1abf72c3398ae3bdbfe3876ef71c86a266c4229966d8170b459d605a20d52a6e
Browse files- README.md +5 -1
- added_tokens.json +6 -33
- config.json +1 -1
- sample_finetune.py +118 -29
- special_tokens_map.json +0 -3
- tokenizer.json +18 -261
- tokenizer_config.json +19 -238
README.md
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- mlx
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license_link: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/LICENSE
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pipeline_tag: text-generation
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---
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# mlx-community/Phi-3-mini-4k-instruct-4bit-no-q-embed
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This model was converted to MLX format from [`microsoft/Phi-3-mini-4k-instruct`]() using mlx-lm version **0.
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Refer to the [original model card](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) for more details on the model.
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## Use with mlx
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- mlx
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license_link: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/LICENSE
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pipeline_tag: text-generation
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widget:
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- messages:
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- role: user
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content: Can you provide ways to eat combinations of bananas and dragonfruits?
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---
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# mlx-community/Phi-3-mini-4k-instruct-4bit-no-q-embed
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This model was converted to MLX format from [`microsoft/Phi-3-mini-4k-instruct`]() using mlx-lm version **0.12.0**.
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Refer to the [original model card](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) for more details on the model.
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## Use with mlx
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added_tokens.json
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"<|endoftext|>": 32000,
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config.json
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"sliding_window":
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.39.3",
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"sliding_window": 2047,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.39.3",
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sample_finetune.py
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import
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from datasets import load_dataset
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from trl import SFTTrainer
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from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments
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"""
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A simple example on using SFTTrainer and Accelerate to finetune Phi-3 models. For
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a more advanced example, please follow HF alignment-handbook/scripts/run_sft.py
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conda install -c conda-forge accelerate
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accelerate config
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accelerate env
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accelerate launch sample_finetune.py
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"""
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###################
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# Hyper-parameters
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###################
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"bf16": True,
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"do_eval": False,
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"learning_rate": 5.0e-06,
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"output_dir": "./checkpoint_dir",
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"overwrite_output_dir": True,
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"per_device_eval_batch_size": 4,
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"per_device_train_batch_size":
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"remove_unused_columns": True,
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"save_steps": 100,
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"save_total_limit": 1,
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"gradient_accumulation_steps": 1,
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"warmup_ratio": 0.2,
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}
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################
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# Modle Loading
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trust_remote_code=True,
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attn_implementation="flash_attention_2", # loading the model with flash-attenstion support
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torch_dtype=torch.bfloat16,
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device_map=
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)
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model = AutoModelForCausalLM.from_pretrained(checkpoint_path, **model_kwargs)
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tokenizer = AutoTokenizer.from_pretrained(checkpoint_path)
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tokenizer.pad_token = tokenizer.unk_token # use unk rather than eos token to prevent endless generation
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tokenizer.pad_token_id = tokenizer.convert_tokens_to_ids(tokenizer.pad_token)
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tokenizer.padding_side = 'right'
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##################
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# Data Processing
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##################
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return example
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raw_dataset = load_dataset("HuggingFaceH4/ultrachat_200k")
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apply_chat_template,
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fn_kwargs={"tokenizer": tokenizer},
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num_proc=
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remove_columns=column_names,
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desc="Applying chat template",
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)
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###########
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# Training
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###########
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trainer = SFTTrainer(
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model=model,
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args=
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max_seq_length=2048,
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dataset_text_field="text",
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tokenizer=tokenizer,
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trainer.save_metrics("train", metrics)
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trainer.save_state()
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#############
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# Evaluation
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#############
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tokenizer.padding_side = 'left'
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metrics = trainer.evaluate()
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metrics["eval_samples"] = len(
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trainer.log_metrics("eval", metrics)
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trainer.save_metrics("eval", metrics)
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#
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import sys
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import logging
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import datasets
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from datasets import load_dataset
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from peft import LoraConfig
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import torch
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import transformers
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from trl import SFTTrainer
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from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments, BitsAndBytesConfig
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"""
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A simple example on using SFTTrainer and Accelerate to finetune Phi-3 models. For
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a more advanced example, please follow HF alignment-handbook/scripts/run_sft.py.
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This example has utilized DeepSpeed ZeRO3 offload to reduce the memory usage. The
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script can be run on V100 or later generation GPUs. Here are some suggestions on
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futher reducing memory consumption:
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- reduce batch size
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- decrease lora dimension
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- restrict lora target modules
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Please follow these steps to run the script:
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1. Install dependencies:
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conda install -c conda-forge accelerate
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pip3 install -i https://pypi.org/simple/ bitsandbytes
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pip3 install peft transformers trl datasets
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pip3 install deepspeed
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2. Setup accelerate and deepspeed config based on the machine used:
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accelerate config
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Here is a sample config for deepspeed zero3:
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compute_environment: LOCAL_MACHINE
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debug: false
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deepspeed_config:
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gradient_accumulation_steps: 1
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offload_optimizer_device: none
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offload_param_device: none
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zero3_init_flag: true
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zero3_save_16bit_model: true
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zero_stage: 3
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distributed_type: DEEPSPEED
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downcast_bf16: 'no'
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enable_cpu_affinity: false
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machine_rank: 0
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main_training_function: main
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mixed_precision: bf16
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num_machines: 1
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num_processes: 4
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rdzv_backend: static
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same_network: true
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tpu_env: []
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tpu_use_cluster: false
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tpu_use_sudo: false
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use_cpu: false
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3. check accelerate config:
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accelerate env
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4. Run the code:
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accelerate launch sample_finetune.py
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"""
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logger = logging.getLogger(__name__)
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###################
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# Hyper-parameters
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###################
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training_config = {
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"bf16": True,
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"do_eval": False,
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"learning_rate": 5.0e-06,
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"output_dir": "./checkpoint_dir",
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"overwrite_output_dir": True,
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"per_device_eval_batch_size": 4,
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"per_device_train_batch_size": 4,
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"remove_unused_columns": True,
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"save_steps": 100,
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"save_total_limit": 1,
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"gradient_accumulation_steps": 1,
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"warmup_ratio": 0.2,
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}
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peft_config = {
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"r": 16,
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"lora_alpha": 32,
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"lora_dropout": 0.05,
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"bias": "none",
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"task_type": "CAUSAL_LM",
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"target_modules": "all-linear",
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"modules_to_save": None,
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}
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train_conf = TrainingArguments(**training_config)
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peft_conf = LoraConfig(**peft_config)
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###############
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# Setup logging
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###############
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logging.basicConfig(
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format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
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datefmt="%Y-%m-%d %H:%M:%S",
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handlers=[logging.StreamHandler(sys.stdout)],
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)
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log_level = train_conf.get_process_log_level()
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logger.setLevel(log_level)
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datasets.utils.logging.set_verbosity(log_level)
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transformers.utils.logging.set_verbosity(log_level)
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transformers.utils.logging.enable_default_handler()
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transformers.utils.logging.enable_explicit_format()
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# Log on each process a small summary
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logger.warning(
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f"Process rank: {train_conf.local_rank}, device: {train_conf.device}, n_gpu: {train_conf.n_gpu}"
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+ f" distributed training: {bool(train_conf.local_rank != -1)}, 16-bits training: {train_conf.fp16}"
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)
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logger.info(f"Training/evaluation parameters {train_conf}")
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logger.info(f"PEFT parameters {peft_conf}")
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################
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# Modle Loading
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trust_remote_code=True,
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attn_implementation="flash_attention_2", # loading the model with flash-attenstion support
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torch_dtype=torch.bfloat16,
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device_map=None
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)
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model = AutoModelForCausalLM.from_pretrained(checkpoint_path, **model_kwargs)
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tokenizer = AutoTokenizer.from_pretrained(checkpoint_path)
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tokenizer.model_max_length = 2048
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tokenizer.pad_token = tokenizer.unk_token # use unk rather than eos token to prevent endless generation
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tokenizer.pad_token_id = tokenizer.convert_tokens_to_ids(tokenizer.pad_token)
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tokenizer.padding_side = 'right'
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##################
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# Data Processing
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##################
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return example
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raw_dataset = load_dataset("HuggingFaceH4/ultrachat_200k")
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train_dataset = raw_dataset["train_sft"]
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test_dataset = raw_dataset["test_sft"]
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column_names = list(train_dataset.features)
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processed_train_dataset = train_dataset.map(
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apply_chat_template,
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fn_kwargs={"tokenizer": tokenizer},
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num_proc=10,
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remove_columns=column_names,
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desc="Applying chat template to train_sft",
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)
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processed_test_dataset = test_dataset.map(
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apply_chat_template,
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fn_kwargs={"tokenizer": tokenizer},
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num_proc=10,
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remove_columns=column_names,
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desc="Applying chat template to test_sft",
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)
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###########
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# Training
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###########
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trainer = SFTTrainer(
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model=model,
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args=train_conf,
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peft_config=peft_conf,
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train_dataset=processed_train_dataset,
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eval_dataset=processed_test_dataset,
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max_seq_length=2048,
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dataset_text_field="text",
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tokenizer=tokenizer,
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trainer.save_metrics("train", metrics)
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trainer.save_state()
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#############
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# Evaluation
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#############
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tokenizer.padding_side = 'left'
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metrics = trainer.evaluate()
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metrics["eval_samples"] = len(processed_test_dataset)
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trainer.log_metrics("eval", metrics)
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trainer.save_metrics("eval", metrics)
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# ############
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# # Save model
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# ############
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trainer.save_model(train_conf.output_dir)
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"<|/inst|>"
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],
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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{
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"bos_token": {
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"content": "<s>",
|
4 |
"lstrip": false,
|
tokenizer.json
CHANGED
@@ -26,9 +26,9 @@
|
|
26 |
"content": "</s>",
|
27 |
"single_word": false,
|
28 |
"lstrip": false,
|
29 |
-
"rstrip":
|
30 |
"normalized": false,
|
31 |
-
"special":
|
32 |
},
|
33 |
{
|
34 |
"id": 32000,
|
@@ -44,43 +44,43 @@
|
|
44 |
"content": "<|assistant|>",
|
45 |
"single_word": false,
|
46 |
"lstrip": false,
|
47 |
-
"rstrip":
|
48 |
"normalized": false,
|
49 |
"special": true
|
50 |
},
|
51 |
{
|
52 |
"id": 32002,
|
53 |
-
"content": "<|
|
54 |
"single_word": false,
|
55 |
"lstrip": false,
|
56 |
-
"rstrip":
|
57 |
"normalized": false,
|
58 |
"special": true
|
59 |
},
|
60 |
{
|
61 |
"id": 32003,
|
62 |
-
"content": "<|
|
63 |
"single_word": false,
|
64 |
"lstrip": false,
|
65 |
-
"rstrip":
|
66 |
"normalized": false,
|
67 |
"special": true
|
68 |
},
|
69 |
{
|
70 |
"id": 32004,
|
71 |
-
"content": "<|
|
72 |
"single_word": false,
|
73 |
"lstrip": false,
|
74 |
-
"rstrip":
|
75 |
"normalized": false,
|
76 |
"special": true
|
77 |
},
|
78 |
{
|
79 |
"id": 32005,
|
80 |
-
"content": "<|
|
81 |
"single_word": false,
|
82 |
"lstrip": false,
|
83 |
-
"rstrip":
|
84 |
"normalized": false,
|
85 |
"special": true
|
86 |
},
|
@@ -89,7 +89,7 @@
|
|
89 |
"content": "<|system|>",
|
90 |
"single_word": false,
|
91 |
"lstrip": false,
|
92 |
-
"rstrip":
|
93 |
"normalized": false,
|
94 |
"special": true
|
95 |
},
|
@@ -98,25 +98,25 @@
|
|
98 |
"content": "<|end|>",
|
99 |
"single_word": false,
|
100 |
"lstrip": false,
|
101 |
-
"rstrip":
|
102 |
"normalized": false,
|
103 |
"special": true
|
104 |
},
|
105 |
{
|
106 |
"id": 32008,
|
107 |
-
"content": "<|
|
108 |
"single_word": false,
|
109 |
"lstrip": false,
|
110 |
-
"rstrip":
|
111 |
"normalized": false,
|
112 |
"special": true
|
113 |
},
|
114 |
{
|
115 |
"id": 32009,
|
116 |
-
"content": "<|
|
117 |
"single_word": false,
|
118 |
"lstrip": false,
|
119 |
-
"rstrip":
|
120 |
"normalized": false,
|
121 |
"special": true
|
122 |
},
|
@@ -125,250 +125,7 @@
|
|
125 |
"content": "<|user|>",
|
126 |
"single_word": false,
|
127 |
"lstrip": false,
|
128 |
-
"rstrip":
|
129 |
-
"normalized": false,
|
130 |
-
"special": true
|
131 |
-
},
|
132 |
-
{
|
133 |
-
"id": 32011,
|
134 |
-
"content": "<|function_list|>",
|
135 |
-
"single_word": false,
|
136 |
-
"lstrip": false,
|
137 |
-
"rstrip": true,
|
138 |
-
"normalized": false,
|
139 |
-
"special": true
|
140 |
-
},
|
141 |
-
{
|
142 |
-
"id": 32012,
|
143 |
-
"content": "<|calc|>",
|
144 |
-
"single_word": false,
|
145 |
-
"lstrip": false,
|
146 |
-
"rstrip": true,
|
147 |
-
"normalized": false,
|
148 |
-
"special": true
|
149 |
-
},
|
150 |
-
{
|
151 |
-
"id": 32013,
|
152 |
-
"content": "<|code|>",
|
153 |
-
"single_word": false,
|
154 |
-
"lstrip": false,
|
155 |
-
"rstrip": true,
|
156 |
-
"normalized": false,
|
157 |
-
"special": true
|
158 |
-
},
|
159 |
-
{
|
160 |
-
"id": 32014,
|
161 |
-
"content": "<|/code|>",
|
162 |
-
"single_word": false,
|
163 |
-
"lstrip": false,
|
164 |
-
"rstrip": true,
|
165 |
-
"normalized": false,
|
166 |
-
"special": true
|
167 |
-
},
|
168 |
-
{
|
169 |
-
"id": 32015,
|
170 |
-
"content": "<|summary|>",
|
171 |
-
"single_word": false,
|
172 |
-
"lstrip": false,
|
173 |
-
"rstrip": true,
|
174 |
-
"normalized": false,
|
175 |
-
"special": true
|
176 |
-
},
|
177 |
-
{
|
178 |
-
"id": 32016,
|
179 |
-
"content": "<|resource|>",
|
180 |
-
"single_word": false,
|
181 |
-
"lstrip": false,
|
182 |
-
"rstrip": true,
|
183 |
-
"normalized": false,
|
184 |
-
"special": true
|
185 |
-
},
|
186 |
-
{
|
187 |
-
"id": 32017,
|
188 |
-
"content": "<|assistant_mask|>",
|
189 |
-
"single_word": false,
|
190 |
-
"lstrip": false,
|
191 |
-
"rstrip": true,
|
192 |
-
"normalized": false,
|
193 |
-
"special": true
|
194 |
-
},
|
195 |
-
{
|
196 |
-
"id": 32018,
|
197 |
-
"content": "<|start|>",
|
198 |
-
"single_word": false,
|
199 |
-
"lstrip": false,
|
200 |
-
"rstrip": true,
|
201 |
-
"normalized": false,
|
202 |
-
"special": true
|
203 |
-
},
|
204 |
-
{
|
205 |
-
"id": 32019,
|
206 |
-
"content": "<|message|>",
|
207 |
-
"single_word": false,
|
208 |
-
"lstrip": false,
|
209 |
-
"rstrip": true,
|
210 |
-
"normalized": false,
|
211 |
-
"special": true
|
212 |
-
},
|
213 |
-
{
|
214 |
-
"id": 32020,
|
215 |
-
"content": "<|fim_prefix|>",
|
216 |
-
"single_word": false,
|
217 |
-
"lstrip": false,
|
218 |
-
"rstrip": true,
|
219 |
-
"normalized": false,
|
220 |
-
"special": true
|
221 |
-
},
|
222 |
-
{
|
223 |
-
"id": 32021,
|
224 |
-
"content": "<|fim_middle|>",
|
225 |
-
"single_word": false,
|
226 |
-
"lstrip": false,
|
227 |
-
"rstrip": true,
|
228 |
-
"normalized": false,
|
229 |
-
"special": true
|
230 |
-
},
|
231 |
-
{
|
232 |
-
"id": 32022,
|
233 |
-
"content": "<|fim_suffix|>",
|
234 |
-
"single_word": false,
|
235 |
-
"lstrip": false,
|
236 |
-
"rstrip": true,
|
237 |
-
"normalized": false,
|
238 |
-
"special": true
|
239 |
-
},
|
240 |
-
{
|
241 |
-
"id": 32023,
|
242 |
-
"content": "<|meta_start|>",
|
243 |
-
"single_word": false,
|
244 |
-
"lstrip": false,
|
245 |
-
"rstrip": true,
|
246 |
-
"normalized": false,
|
247 |
-
"special": true
|
248 |
-
},
|
249 |
-
{
|
250 |
-
"id": 32024,
|
251 |
-
"content": "<|ipynb_marker|>",
|
252 |
-
"single_word": false,
|
253 |
-
"lstrip": false,
|
254 |
-
"rstrip": true,
|
255 |
-
"normalized": false,
|
256 |
-
"special": true
|
257 |
-
},
|
258 |
-
{
|
259 |
-
"id": 32025,
|
260 |
-
"content": "<|diff_marker|>",
|
261 |
-
"single_word": false,
|
262 |
-
"lstrip": false,
|
263 |
-
"rstrip": true,
|
264 |
-
"normalized": false,
|
265 |
-
"special": true
|
266 |
-
},
|
267 |
-
{
|
268 |
-
"id": 32026,
|
269 |
-
"content": "<|ghissue|>",
|
270 |
-
"single_word": false,
|
271 |
-
"lstrip": false,
|
272 |
-
"rstrip": true,
|
273 |
-
"normalized": false,
|
274 |
-
"special": true
|
275 |
-
},
|
276 |
-
{
|
277 |
-
"id": 32027,
|
278 |
-
"content": "<|ghreview|>",
|
279 |
-
"single_word": false,
|
280 |
-
"lstrip": false,
|
281 |
-
"rstrip": true,
|
282 |
-
"normalized": false,
|
283 |
-
"special": true
|
284 |
-
},
|
285 |
-
{
|
286 |
-
"id": 32028,
|
287 |
-
"content": "<|disc_start|>",
|
288 |
-
"single_word": false,
|
289 |
-
"lstrip": false,
|
290 |
-
"rstrip": true,
|
291 |
-
"normalized": false,
|
292 |
-
"special": true
|
293 |
-
},
|
294 |
-
{
|
295 |
-
"id": 32029,
|
296 |
-
"content": "<|disc_sep|>",
|
297 |
-
"single_word": false,
|
298 |
-
"lstrip": false,
|
299 |
-
"rstrip": true,
|
300 |
-
"normalized": false,
|
301 |
-
"special": true
|
302 |
-
},
|
303 |
-
{
|
304 |
-
"id": 32030,
|
305 |
-
"content": "<|disc_thread|><|query|>",
|
306 |
-
"single_word": false,
|
307 |
-
"lstrip": false,
|
308 |
-
"rstrip": true,
|
309 |
-
"normalized": false,
|
310 |
-
"special": true
|
311 |
-
},
|
312 |
-
{
|
313 |
-
"id": 32031,
|
314 |
-
"content": "<|/query|>",
|
315 |
-
"single_word": false,
|
316 |
-
"lstrip": false,
|
317 |
-
"rstrip": true,
|
318 |
-
"normalized": false,
|
319 |
-
"special": true
|
320 |
-
},
|
321 |
-
{
|
322 |
-
"id": 32032,
|
323 |
-
"content": "<|data|>",
|
324 |
-
"single_word": false,
|
325 |
-
"lstrip": false,
|
326 |
-
"rstrip": true,
|
327 |
-
"normalized": false,
|
328 |
-
"special": true
|
329 |
-
},
|
330 |
-
{
|
331 |
-
"id": 32033,
|
332 |
-
"content": "<|/data|>",
|
333 |
-
"single_word": false,
|
334 |
-
"lstrip": false,
|
335 |
-
"rstrip": true,
|
336 |
-
"normalized": false,
|
337 |
-
"special": true
|
338 |
-
},
|
339 |
-
{
|
340 |
-
"id": 32034,
|
341 |
-
"content": "<|sys|>",
|
342 |
-
"single_word": false,
|
343 |
-
"lstrip": false,
|
344 |
-
"rstrip": true,
|
345 |
-
"normalized": false,
|
346 |
-
"special": true
|
347 |
-
},
|
348 |
-
{
|
349 |
-
"id": 32035,
|
350 |
-
"content": "<|/sys|>",
|
351 |
-
"single_word": false,
|
352 |
-
"lstrip": false,
|
353 |
-
"rstrip": true,
|
354 |
-
"normalized": false,
|
355 |
-
"special": true
|
356 |
-
},
|
357 |
-
{
|
358 |
-
"id": 32036,
|
359 |
-
"content": "<|inst|>",
|
360 |
-
"single_word": false,
|
361 |
-
"lstrip": false,
|
362 |
-
"rstrip": true,
|
363 |
-
"normalized": false,
|
364 |
-
"special": true
|
365 |
-
},
|
366 |
-
{
|
367 |
-
"id": 32037,
|
368 |
-
"content": "<|/inst|>",
|
369 |
-
"single_word": false,
|
370 |
-
"lstrip": false,
|
371 |
-
"rstrip": true,
|
372 |
"normalized": false,
|
373 |
"special": true
|
374 |
}
|
|
|
26 |
"content": "</s>",
|
27 |
"single_word": false,
|
28 |
"lstrip": false,
|
29 |
+
"rstrip": false,
|
30 |
"normalized": false,
|
31 |
+
"special": true
|
32 |
},
|
33 |
{
|
34 |
"id": 32000,
|
|
|
44 |
"content": "<|assistant|>",
|
45 |
"single_word": false,
|
46 |
"lstrip": false,
|
47 |
+
"rstrip": false,
|
48 |
"normalized": false,
|
49 |
"special": true
|
50 |
},
|
51 |
{
|
52 |
"id": 32002,
|
53 |
+
"content": "<|placeholder1|>",
|
54 |
"single_word": false,
|
55 |
"lstrip": false,
|
56 |
+
"rstrip": false,
|
57 |
"normalized": false,
|
58 |
"special": true
|
59 |
},
|
60 |
{
|
61 |
"id": 32003,
|
62 |
+
"content": "<|placeholder2|>",
|
63 |
"single_word": false,
|
64 |
"lstrip": false,
|
65 |
+
"rstrip": false,
|
66 |
"normalized": false,
|
67 |
"special": true
|
68 |
},
|
69 |
{
|
70 |
"id": 32004,
|
71 |
+
"content": "<|placeholder3|>",
|
72 |
"single_word": false,
|
73 |
"lstrip": false,
|
74 |
+
"rstrip": false,
|
75 |
"normalized": false,
|
76 |
"special": true
|
77 |
},
|
78 |
{
|
79 |
"id": 32005,
|
80 |
+
"content": "<|placeholder4|>",
|
81 |
"single_word": false,
|
82 |
"lstrip": false,
|
83 |
+
"rstrip": false,
|
84 |
"normalized": false,
|
85 |
"special": true
|
86 |
},
|
|
|
89 |
"content": "<|system|>",
|
90 |
"single_word": false,
|
91 |
"lstrip": false,
|
92 |
+
"rstrip": false,
|
93 |
"normalized": false,
|
94 |
"special": true
|
95 |
},
|
|
|
98 |
"content": "<|end|>",
|
99 |
"single_word": false,
|
100 |
"lstrip": false,
|
101 |
+
"rstrip": false,
|
102 |
"normalized": false,
|
103 |
"special": true
|
104 |
},
|
105 |
{
|
106 |
"id": 32008,
|
107 |
+
"content": "<|placeholder5|>",
|
108 |
"single_word": false,
|
109 |
"lstrip": false,
|
110 |
+
"rstrip": false,
|
111 |
"normalized": false,
|
112 |
"special": true
|
113 |
},
|
114 |
{
|
115 |
"id": 32009,
|
116 |
+
"content": "<|placeholder6|>",
|
117 |
"single_word": false,
|
118 |
"lstrip": false,
|
119 |
+
"rstrip": false,
|
120 |
"normalized": false,
|
121 |
"special": true
|
122 |
},
|
|
|
125 |
"content": "<|user|>",
|
126 |
"single_word": false,
|
127 |
"lstrip": false,
|
128 |
+
"rstrip": false,
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
129 |
"normalized": false,
|
130 |
"special": true
|
131 |
}
|
tokenizer_config.json
CHANGED
@@ -22,9 +22,9 @@
|
|
22 |
"content": "</s>",
|
23 |
"lstrip": false,
|
24 |
"normalized": false,
|
25 |
-
"rstrip":
|
26 |
"single_word": false,
|
27 |
-
"special":
|
28 |
},
|
29 |
"32000": {
|
30 |
"content": "<|endoftext|>",
|
@@ -38,39 +38,39 @@
|
|
38 |
"content": "<|assistant|>",
|
39 |
"lstrip": false,
|
40 |
"normalized": false,
|
41 |
-
"rstrip":
|
42 |
"single_word": false,
|
43 |
"special": true
|
44 |
},
|
45 |
"32002": {
|
46 |
-
"content": "<|
|
47 |
"lstrip": false,
|
48 |
"normalized": false,
|
49 |
-
"rstrip":
|
50 |
"single_word": false,
|
51 |
"special": true
|
52 |
},
|
53 |
"32003": {
|
54 |
-
"content": "<|
|
55 |
"lstrip": false,
|
56 |
"normalized": false,
|
57 |
-
"rstrip":
|
58 |
"single_word": false,
|
59 |
"special": true
|
60 |
},
|
61 |
"32004": {
|
62 |
-
"content": "<|
|
63 |
"lstrip": false,
|
64 |
"normalized": false,
|
65 |
-
"rstrip":
|
66 |
"single_word": false,
|
67 |
"special": true
|
68 |
},
|
69 |
"32005": {
|
70 |
-
"content": "<|
|
71 |
"lstrip": false,
|
72 |
"normalized": false,
|
73 |
-
"rstrip":
|
74 |
"single_word": false,
|
75 |
"special": true
|
76 |
},
|
@@ -78,7 +78,7 @@
|
|
78 |
"content": "<|system|>",
|
79 |
"lstrip": false,
|
80 |
"normalized": false,
|
81 |
-
"rstrip":
|
82 |
"single_word": false,
|
83 |
"special": true
|
84 |
},
|
@@ -86,23 +86,23 @@
|
|
86 |
"content": "<|end|>",
|
87 |
"lstrip": false,
|
88 |
"normalized": false,
|
89 |
-
"rstrip":
|
90 |
"single_word": false,
|
91 |
"special": true
|
92 |
},
|
93 |
"32008": {
|
94 |
-
"content": "<|
|
95 |
"lstrip": false,
|
96 |
"normalized": false,
|
97 |
-
"rstrip":
|
98 |
"single_word": false,
|
99 |
"special": true
|
100 |
},
|
101 |
"32009": {
|
102 |
-
"content": "<|
|
103 |
"lstrip": false,
|
104 |
"normalized": false,
|
105 |
-
"rstrip":
|
106 |
"single_word": false,
|
107 |
"special": true
|
108 |
},
|
@@ -110,232 +110,13 @@
|
|
110 |
"content": "<|user|>",
|
111 |
"lstrip": false,
|
112 |
"normalized": false,
|
113 |
-
"rstrip":
|
114 |
-
"single_word": false,
|
115 |
-
"special": true
|
116 |
-
},
|
117 |
-
"32011": {
|
118 |
-
"content": "<|function_list|>",
|
119 |
-
"lstrip": false,
|
120 |
-
"normalized": false,
|
121 |
-
"rstrip": true,
|
122 |
-
"single_word": false,
|
123 |
-
"special": true
|
124 |
-
},
|
125 |
-
"32012": {
|
126 |
-
"content": "<|calc|>",
|
127 |
-
"lstrip": false,
|
128 |
-
"normalized": false,
|
129 |
-
"rstrip": true,
|
130 |
-
"single_word": false,
|
131 |
-
"special": true
|
132 |
-
},
|
133 |
-
"32013": {
|
134 |
-
"content": "<|code|>",
|
135 |
-
"lstrip": false,
|
136 |
-
"normalized": false,
|
137 |
-
"rstrip": true,
|
138 |
-
"single_word": false,
|
139 |
-
"special": true
|
140 |
-
},
|
141 |
-
"32014": {
|
142 |
-
"content": "<|/code|>",
|
143 |
-
"lstrip": false,
|
144 |
-
"normalized": false,
|
145 |
-
"rstrip": true,
|
146 |
-
"single_word": false,
|
147 |
-
"special": true
|
148 |
-
},
|
149 |
-
"32015": {
|
150 |
-
"content": "<|summary|>",
|
151 |
-
"lstrip": false,
|
152 |
-
"normalized": false,
|
153 |
-
"rstrip": true,
|
154 |
-
"single_word": false,
|
155 |
-
"special": true
|
156 |
-
},
|
157 |
-
"32016": {
|
158 |
-
"content": "<|resource|>",
|
159 |
-
"lstrip": false,
|
160 |
-
"normalized": false,
|
161 |
-
"rstrip": true,
|
162 |
-
"single_word": false,
|
163 |
-
"special": true
|
164 |
-
},
|
165 |
-
"32017": {
|
166 |
-
"content": "<|assistant_mask|>",
|
167 |
-
"lstrip": false,
|
168 |
-
"normalized": false,
|
169 |
-
"rstrip": true,
|
170 |
-
"single_word": false,
|
171 |
-
"special": true
|
172 |
-
},
|
173 |
-
"32018": {
|
174 |
-
"content": "<|start|>",
|
175 |
-
"lstrip": false,
|
176 |
-
"normalized": false,
|
177 |
-
"rstrip": true,
|
178 |
-
"single_word": false,
|
179 |
-
"special": true
|
180 |
-
},
|
181 |
-
"32019": {
|
182 |
-
"content": "<|message|>",
|
183 |
-
"lstrip": false,
|
184 |
-
"normalized": false,
|
185 |
-
"rstrip": true,
|
186 |
-
"single_word": false,
|
187 |
-
"special": true
|
188 |
-
},
|
189 |
-
"32020": {
|
190 |
-
"content": "<|fim_prefix|>",
|
191 |
-
"lstrip": false,
|
192 |
-
"normalized": false,
|
193 |
-
"rstrip": true,
|
194 |
-
"single_word": false,
|
195 |
-
"special": true
|
196 |
-
},
|
197 |
-
"32021": {
|
198 |
-
"content": "<|fim_middle|>",
|
199 |
-
"lstrip": false,
|
200 |
-
"normalized": false,
|
201 |
-
"rstrip": true,
|
202 |
-
"single_word": false,
|
203 |
-
"special": true
|
204 |
-
},
|
205 |
-
"32022": {
|
206 |
-
"content": "<|fim_suffix|>",
|
207 |
-
"lstrip": false,
|
208 |
-
"normalized": false,
|
209 |
-
"rstrip": true,
|
210 |
-
"single_word": false,
|
211 |
-
"special": true
|
212 |
-
},
|
213 |
-
"32023": {
|
214 |
-
"content": "<|meta_start|>",
|
215 |
-
"lstrip": false,
|
216 |
-
"normalized": false,
|
217 |
-
"rstrip": true,
|
218 |
-
"single_word": false,
|
219 |
-
"special": true
|
220 |
-
},
|
221 |
-
"32024": {
|
222 |
-
"content": "<|ipynb_marker|>",
|
223 |
-
"lstrip": false,
|
224 |
-
"normalized": false,
|
225 |
-
"rstrip": true,
|
226 |
-
"single_word": false,
|
227 |
-
"special": true
|
228 |
-
},
|
229 |
-
"32025": {
|
230 |
-
"content": "<|diff_marker|>",
|
231 |
-
"lstrip": false,
|
232 |
-
"normalized": false,
|
233 |
-
"rstrip": true,
|
234 |
-
"single_word": false,
|
235 |
-
"special": true
|
236 |
-
},
|
237 |
-
"32026": {
|
238 |
-
"content": "<|ghissue|>",
|
239 |
-
"lstrip": false,
|
240 |
-
"normalized": false,
|
241 |
-
"rstrip": true,
|
242 |
-
"single_word": false,
|
243 |
-
"special": true
|
244 |
-
},
|
245 |
-
"32027": {
|
246 |
-
"content": "<|ghreview|>",
|
247 |
-
"lstrip": false,
|
248 |
-
"normalized": false,
|
249 |
-
"rstrip": true,
|
250 |
-
"single_word": false,
|
251 |
-
"special": true
|
252 |
-
},
|
253 |
-
"32028": {
|
254 |
-
"content": "<|disc_start|>",
|
255 |
-
"lstrip": false,
|
256 |
-
"normalized": false,
|
257 |
-
"rstrip": true,
|
258 |
-
"single_word": false,
|
259 |
-
"special": true
|
260 |
-
},
|
261 |
-
"32029": {
|
262 |
-
"content": "<|disc_sep|>",
|
263 |
-
"lstrip": false,
|
264 |
-
"normalized": false,
|
265 |
-
"rstrip": true,
|
266 |
-
"single_word": false,
|
267 |
-
"special": true
|
268 |
-
},
|
269 |
-
"32030": {
|
270 |
-
"content": "<|disc_thread|><|query|>",
|
271 |
-
"lstrip": false,
|
272 |
-
"normalized": false,
|
273 |
-
"rstrip": true,
|
274 |
-
"single_word": false,
|
275 |
-
"special": true
|
276 |
-
},
|
277 |
-
"32031": {
|
278 |
-
"content": "<|/query|>",
|
279 |
-
"lstrip": false,
|
280 |
-
"normalized": false,
|
281 |
-
"rstrip": true,
|
282 |
-
"single_word": false,
|
283 |
-
"special": true
|
284 |
-
},
|
285 |
-
"32032": {
|
286 |
-
"content": "<|data|>",
|
287 |
-
"lstrip": false,
|
288 |
-
"normalized": false,
|
289 |
-
"rstrip": true,
|
290 |
-
"single_word": false,
|
291 |
-
"special": true
|
292 |
-
},
|
293 |
-
"32033": {
|
294 |
-
"content": "<|/data|>",
|
295 |
-
"lstrip": false,
|
296 |
-
"normalized": false,
|
297 |
-
"rstrip": true,
|
298 |
-
"single_word": false,
|
299 |
-
"special": true
|
300 |
-
},
|
301 |
-
"32034": {
|
302 |
-
"content": "<|sys|>",
|
303 |
-
"lstrip": false,
|
304 |
-
"normalized": false,
|
305 |
-
"rstrip": true,
|
306 |
-
"single_word": false,
|
307 |
-
"special": true
|
308 |
-
},
|
309 |
-
"32035": {
|
310 |
-
"content": "<|/sys|>",
|
311 |
-
"lstrip": false,
|
312 |
-
"normalized": false,
|
313 |
-
"rstrip": true,
|
314 |
-
"single_word": false,
|
315 |
-
"special": true
|
316 |
-
},
|
317 |
-
"32036": {
|
318 |
-
"content": "<|inst|>",
|
319 |
-
"lstrip": false,
|
320 |
-
"normalized": false,
|
321 |
-
"rstrip": true,
|
322 |
-
"single_word": false,
|
323 |
-
"special": true
|
324 |
-
},
|
325 |
-
"32037": {
|
326 |
-
"content": "<|/inst|>",
|
327 |
-
"lstrip": false,
|
328 |
-
"normalized": false,
|
329 |
-
"rstrip": true,
|
330 |
"single_word": false,
|
331 |
"special": true
|
332 |
}
|
333 |
},
|
334 |
-
"additional_special_tokens": [
|
335 |
-
"<|/inst|>"
|
336 |
-
],
|
337 |
"bos_token": "<s>",
|
338 |
-
"chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == '
|
339 |
"clean_up_tokenization_spaces": false,
|
340 |
"eos_token": "<|endoftext|>",
|
341 |
"legacy": false,
|
|
|
22 |
"content": "</s>",
|
23 |
"lstrip": false,
|
24 |
"normalized": false,
|
25 |
+
"rstrip": false,
|
26 |
"single_word": false,
|
27 |
+
"special": true
|
28 |
},
|
29 |
"32000": {
|
30 |
"content": "<|endoftext|>",
|
|
|
38 |
"content": "<|assistant|>",
|
39 |
"lstrip": false,
|
40 |
"normalized": false,
|
41 |
+
"rstrip": false,
|
42 |
"single_word": false,
|
43 |
"special": true
|
44 |
},
|
45 |
"32002": {
|
46 |
+
"content": "<|placeholder1|>",
|
47 |
"lstrip": false,
|
48 |
"normalized": false,
|
49 |
+
"rstrip": false,
|
50 |
"single_word": false,
|
51 |
"special": true
|
52 |
},
|
53 |
"32003": {
|
54 |
+
"content": "<|placeholder2|>",
|
55 |
"lstrip": false,
|
56 |
"normalized": false,
|
57 |
+
"rstrip": false,
|
58 |
"single_word": false,
|
59 |
"special": true
|
60 |
},
|
61 |
"32004": {
|
62 |
+
"content": "<|placeholder3|>",
|
63 |
"lstrip": false,
|
64 |
"normalized": false,
|
65 |
+
"rstrip": false,
|
66 |
"single_word": false,
|
67 |
"special": true
|
68 |
},
|
69 |
"32005": {
|
70 |
+
"content": "<|placeholder4|>",
|
71 |
"lstrip": false,
|
72 |
"normalized": false,
|
73 |
+
"rstrip": false,
|
74 |
"single_word": false,
|
75 |
"special": true
|
76 |
},
|
|
|
78 |
"content": "<|system|>",
|
79 |
"lstrip": false,
|
80 |
"normalized": false,
|
81 |
+
"rstrip": false,
|
82 |
"single_word": false,
|
83 |
"special": true
|
84 |
},
|
|
|
86 |
"content": "<|end|>",
|
87 |
"lstrip": false,
|
88 |
"normalized": false,
|
89 |
+
"rstrip": false,
|
90 |
"single_word": false,
|
91 |
"special": true
|
92 |
},
|
93 |
"32008": {
|
94 |
+
"content": "<|placeholder5|>",
|
95 |
"lstrip": false,
|
96 |
"normalized": false,
|
97 |
+
"rstrip": false,
|
98 |
"single_word": false,
|
99 |
"special": true
|
100 |
},
|
101 |
"32009": {
|
102 |
+
"content": "<|placeholder6|>",
|
103 |
"lstrip": false,
|
104 |
"normalized": false,
|
105 |
+
"rstrip": false,
|
106 |
"single_word": false,
|
107 |
"special": true
|
108 |
},
|
|
|
110 |
"content": "<|user|>",
|
111 |
"lstrip": false,
|
112 |
"normalized": false,
|
113 |
+
"rstrip": false,
|
|
|
|
|
|
|
|
|
|
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|
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|
114 |
"single_word": false,
|
115 |
"special": true
|
116 |
}
|
117 |
},
|
|
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|
118 |
"bos_token": "<s>",
|
119 |
+
"chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') %}{{'<|user|>' + '\n' + message['content'] + '<|end|>' + '\n' + '<|assistant|>' + '\n'}}{% elif (message['role'] == 'assistant') %}{{message['content'] + '<|end|>' + '\n'}}{% endif %}{% endfor %}",
|
120 |
"clean_up_tokenization_spaces": false,
|
121 |
"eos_token": "<|endoftext|>",
|
122 |
"legacy": false,
|