upload model
Browse files- README.md +91 -0
- README_zh-CN.md +86 -0
- added_tokens.json +6 -0
- config.json +26 -0
- generation_config.json +10 -0
- model.safetensors +3 -0
- special_tokens_map.json +36 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +83 -0
README.md
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---
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license: gpl-3.0
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---
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---
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license: gpl-3.0
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language:
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- en
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---
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# NanoLM-25M-Instruct-v1
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English | [简体中文](README_zh-CN.md)
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## Introduction
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In order to explore the potential of small models, I have attempted to build a series of them, which are available in the [NanoLM Collections](https://huggingface.co/collections/Mxode/nanolm-66d6d75b4a69536bca2705b2).
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This is NanoLM-25M-Instruct-v1. The model currently supports **English only**.
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## Model Details
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| Nano LMs | Non-emb Params | Arch | Layers | Dim | Heads | Seq Len |
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| :----------: | :------------------: | :---: | :----: | :-------: | :---: | :---: |
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| **25M** | **15M** | **MistralForCausalLM** | **12** | **312** | **12** | **2K** |
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| 70M | 42M | LlamaForCausalLM | 12 | 576 | 9 |2K|
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| 0.3B | 180M | Qwen2ForCausalLM | 12 | 896 | 14 |4K|
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| 1B | 840M | Qwen2ForCausalLM | 18 | 1536 | 12 |4K|
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## How to use
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_path = 'Mxode/NanoLM-25M-Instruct-v1'
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model = AutoModelForCausalLM.from_pretrained(model_path).to('cuda:0', torch.bfloat16)
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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def get_response(prompt: str, **kwargs):
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generation_args = dict(
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max_new_tokens = kwargs.pop("max_new_tokens", 512),
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do_sample = kwargs.pop("do_sample", True),
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temperature = kwargs.pop("temperature", 0.7),
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top_p = kwargs.pop("top_p", 0.8),
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top_k = kwargs.pop("top_k", 40),
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**kwargs
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)
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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generated_ids = model.generate(model_inputs.input_ids, **generation_args)
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generated_ids = [
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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return response
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prompt1 = "What can you do for me?"
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print(get_response(prompt1, do_sample=False))
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"""
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I'm so glad you asked! I'm a large language model, so I don't have personal experiences or emotions, but I can provide information and assist with tasks to help with your tasks.
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Here are some ways I can assist you:
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1. **Answer questions**: I can provide information on a wide range of topics, from science and history to entertainment and culture.
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2. **Generate text**: I can create text based on a prompt or topic, and can even help with writing tasks such as proofreading and editing.
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3. **Translate text**: I can translate text from one language to another, including popular languages such as Spanish, French, German, Chinese, and many more.
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4. **Summarize content**: I can summarize long pieces of text, such as articles or documents, into shorter, more digestible versions.
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5. **Offer suggestions**: I can provide suggestions for things like gift ideas, travel destinations, books, or movies.
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6. **Chat and converse**: I can engage in natural-sounding conversations, using context and understanding to respond to questions and statements.
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7. **Play games**: I can play simple text-based games, such as 20 Questions, Hangman, or Word Jumble.
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8. **Provide definitions**: I can define words and phrases, explaining their meanings and usage.
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9. **Offer suggestions**: I can provide suggestions for things like gift ideas, travel destinations, or books to read.
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10. **Entertain**: I can engage in fun conversations, tell jokes, and even create simple games or puzzles.
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Which of these methods would you like to do?
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"""
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```
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README_zh-CN.md
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# NanoLM-25M-Instruct-v1
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[English](README.md) | 简体中文
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## Introduction
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7 |
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为了探究小模型的潜能,我尝试构建一系列小模型,并存放于 [NanoLM Collections](https://huggingface.co/collections/Mxode/nanolm-66d6d75b4a69536bca2705b2)。
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这是 NanoLM-25M-Instruct-v1。该模型目前仅支持**英文**。
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## 模型详情
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| Nano LMs | Non-emb Params | Arch | Layers | Dim | Heads | Seq Len |
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16 |
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| :----------: | :------------------: | :---: | :----: | :-------: | :---: | :---: |
|
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+
| **25M** | **15M** | **MistralForCausalLM** | **12** | **312** | **12** | **2K** |
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18 |
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| 70M | 42M | LlamaForCausalLM | 12 | 576 | 9 |2K|
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19 |
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| 0.3B | 180M | Qwen2ForCausalLM | 12 | 896 | 14 |4K|
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| 1B | 840M | Qwen2ForCausalLM | 18 | 1536 | 12 |4K|
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## 如何使用
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24 |
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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model_path = 'Mxode/NanoLM-25M-Instruct-v1'
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model = AutoModelForCausalLM.from_pretrained(model_path).to('cuda:0', torch.bfloat16)
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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def get_response(prompt: str, **kwargs):
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generation_args = dict(
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max_new_tokens = kwargs.pop("max_new_tokens", 512),
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do_sample = kwargs.pop("do_sample", True),
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temperature = kwargs.pop("temperature", 0.7),
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top_p = kwargs.pop("top_p", 0.8),
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top_k = kwargs.pop("top_k", 40),
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**kwargs
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)
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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generated_ids = model.generate(model_inputs.input_ids, **generation_args)
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generated_ids = [
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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return response
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prompt1 = "What can you do for me?"
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print(get_response(prompt1, do_sample=False))
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+
|
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"""
|
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+
I'm so glad you asked! I'm a large language model, so I don't have personal experiences or emotions, but I can provide information and assist with tasks to help with your tasks.
|
70 |
+
|
71 |
+
Here are some ways I can assist you:
|
72 |
+
|
73 |
+
1. **Answer questions**: I can provide information on a wide range of topics, from science and history to entertainment and culture.
|
74 |
+
2. **Generate text**: I can create text based on a prompt or topic, and can even help with writing tasks such as proofreading and editing.
|
75 |
+
3. **Translate text**: I can translate text from one language to another, including popular languages such as Spanish, French, German, Chinese, and many more.
|
76 |
+
4. **Summarize content**: I can summarize long pieces of text, such as articles or documents, into shorter, more digestible versions.
|
77 |
+
5. **Offer suggestions**: I can provide suggestions for things like gift ideas, travel destinations, books, or movies.
|
78 |
+
6. **Chat and converse**: I can engage in natural-sounding conversations, using context and understanding to respond to questions and statements.
|
79 |
+
7. **Play games**: I can play simple text-based games, such as 20 Questions, Hangman, or Word Jumble.
|
80 |
+
8. **Provide definitions**: I can define words and phrases, explaining their meanings and usage.
|
81 |
+
9. **Offer suggestions**: I can provide suggestions for things like gift ideas, travel destinations, or books to read.
|
82 |
+
10. **Entertain**: I can engage in fun conversations, tell jokes, and even create simple games or puzzles.
|
83 |
+
|
84 |
+
Which of these methods would you like to do?
|
85 |
+
"""
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```
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added_tokens.json
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{
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"<image>": 32003,
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"<|endoftext|>": 32002,
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"<|im_end|>": 32001,
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"<|im_start|>": 32000
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}
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config.json
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{
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"_name_or_path": "Mxode/NanoLM-25M-Instruct-v1",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 32001,
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"hidden_act": "silu",
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"hidden_size": 312,
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"initializer_range": 0.02,
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"intermediate_size": 1092,
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"max_position_embeddings": 2048,
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"model_type": "mistral",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"num_key_value_heads": 4,
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"rms_norm_eps": 1e-06,
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"rope_theta": 10000.0,
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"sliding_window": null,
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"tie_word_embeddings": true,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.42.0",
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"use_cache": false,
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"vocab_size": 32064
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}
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generation_config.json
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{
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"do_sample": true,
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"eos_token_id": 32001,
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"max_new_tokens": 2048,
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"pad_token_id": 32002,
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"temperature": 0.3,
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"top_k": 20,
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"top_p": 0.7,
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"transformers_version": "4.42.0"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7a0e1d819ee06353704cc39bfcddad8f11fdee964457a2503be667fe7ff48e80
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size 50796360
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special_tokens_map.json
ADDED
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{
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"additional_special_tokens": [
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"<|im_start|>",
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"<|im_end|>",
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"<|endoftext|>",
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"<image>"
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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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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|im_end|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": false,
|
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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+
"lstrip": false,
|
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+
"normalized": false,
|
33 |
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"rstrip": false,
|
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"single_word": false
|
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}
|
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+
}
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tokenizer.json
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See raw diff
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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size 493443
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tokenizer_config.json
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+
{
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+
"add_bos_token": false,
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3 |
+
"add_eos_token": false,
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4 |
+
"add_prefix_space": null,
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5 |
+
"added_tokens_decoder": {
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"0": {
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"content": "<unk>",
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+
"lstrip": false,
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9 |
+
"normalized": false,
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+
"rstrip": false,
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11 |
+
"single_word": false,
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12 |
+
"special": true
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},
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+
"1": {
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+
"content": "<s>",
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+
"lstrip": false,
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+
"normalized": false,
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+
"rstrip": false,
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+
"single_word": false,
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+
"special": true
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},
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"2": {
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"content": "</s>",
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+
"lstrip": false,
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+
"normalized": false,
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+
"rstrip": false,
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+
"single_word": false,
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+
"special": true
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},
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"32000": {
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"content": "<|im_start|>",
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"lstrip": false,
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+
"normalized": false,
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+
"rstrip": false,
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+
"single_word": false,
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"special": true
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},
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+
"32001": {
|
39 |
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"content": "<|im_end|>",
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40 |
+
"lstrip": false,
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41 |
+
"normalized": false,
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42 |
+
"rstrip": false,
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43 |
+
"single_word": false,
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44 |
+
"special": true
|
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+
},
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+
"32002": {
|
47 |
+
"content": "<|endoftext|>",
|
48 |
+
"lstrip": false,
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+
"normalized": false,
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+
"rstrip": false,
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+
"single_word": false,
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52 |
+
"special": true
|
53 |
+
},
|
54 |
+
"32003": {
|
55 |
+
"content": "<image>",
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56 |
+
"lstrip": false,
|
57 |
+
"normalized": false,
|
58 |
+
"rstrip": false,
|
59 |
+
"single_word": false,
|
60 |
+
"special": true
|
61 |
+
}
|
62 |
+
},
|
63 |
+
"additional_special_tokens": [
|
64 |
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"<|im_start|>",
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"<|im_end|>",
|
66 |
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"<|endoftext|>",
|
67 |
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"<image>"
|
68 |
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],
|
69 |
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"bos_token": "<s>",
|
70 |
+
"chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
71 |
+
"clean_up_tokenization_spaces": false,
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72 |
+
"eos_token": "<|im_end|>",
|
73 |
+
"errors": "replace",
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74 |
+
"legacy": true,
|
75 |
+
"model_max_length": 2048,
|
76 |
+
"pad_token": "<|endoftext|>",
|
77 |
+
"padding_side": "left",
|
78 |
+
"sp_model_kwargs": {},
|
79 |
+
"spaces_between_special_tokens": false,
|
80 |
+
"tokenizer_class": "LlamaTokenizer",
|
81 |
+
"unk_token": "<unk>",
|
82 |
+
"use_default_system_prompt": false
|
83 |
+
}
|