Triangle104
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---
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license: apache-2.0
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language:
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- en
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tags:
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- chat
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- llama-cpp
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- gguf-my-repo
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pipeline_tag: text-generation
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library_name: transformers
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base_model: anthracite-org/magnum-v4-12b
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---
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# Triangle104/magnum-v4-12b-Q4_K_S-GGUF
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This model was converted to GGUF format from [`anthracite-org/magnum-v4-12b`](https://huggingface.co/anthracite-org/magnum-v4-12b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/anthracite-org/magnum-v4-12b) for more details on the model.
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---
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Model details:
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This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus.
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This model is fine-tuned on top of mistralai/Mistral-Nemo-Instruct-2407.
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Prompting
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A typical input would look like this:
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<s>[INST] SYSTEM MESSAGE
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USER MESSAGE[/INST] ASSISTANT MESSAGE</s>[INST] USER MESSAGE[/INST]
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SillyTavern templates
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Below are Instruct and Context templates for use within SillyTavern.
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context template
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default SillyTavern template works fine
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instruct template
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default SillyTavern template works fine
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Axolotl config
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See axolotl config
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base_model: mistralai/Mistral-Nemo-Instruct-2407
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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hub_model_id: anthracite-org/magnum-v4-12b-r2
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hub_strategy: "all_checkpoints"
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push_dataset_to_hub:
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hf_use_auth_token: true
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_swiglu: true
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liger_fused_linear_cross_entropy: true
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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datasets:
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- path: anthracite-org/c2_logs_32k_llama3_qwen2_v1.2_no_system
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type: custommistralv3tekken
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- path: anthracite-org/kalo-opus-instruct-22k-no-refusal-no-system
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type: custommistralv3tekken
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- path: anthracite-org/kalo-opus-instruct-3k-filtered-no-system
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type: custommistralv3tekken
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- path: anthracite-org/nopm_claude_writing_fixed
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type: custommistralv3tekken
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- path: anthracite-org/kalo_opus_misc_240827_no_system
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type: custommistralv3tekken
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- path: anthracite-org/kalo_misc_part2_no_system
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type: custommistralv3tekken
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#chat_template: chatml
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shuffle_merged_datasets: true
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#default_system_message: "You are an assistant that responds to the user."
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dataset_prepared_path: /workspace/data/magnum-12b-data
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val_set_size: 0.0
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output_dir: /workspace/data/12b-fft-out
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sequence_len: 32768
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sample_packing: true
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pad_to_sequence_len: true
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adapter:
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lora_model_dir:
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lora_r:
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lora_alpha:
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lora_dropout:
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lora_target_linear:
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lora_fan_in_fan_out:
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wandb_project: 12b-magnum-fft
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wandb_entity:
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wandb_watch:
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wandb_name: v4-r2-attempt-01
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wandb_log_model:
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gradient_accumulation_steps: 2
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micro_batch_size: 1
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num_epochs: 2
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.00001
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 40
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evals_per_epoch:
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eval_table_size:
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eval_max_new_tokens:
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saves_per_epoch: 2
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debug:
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deepspeed: deepspeed_configs/zero2.json
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weight_decay: 0.1
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: <pad>
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Credits
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We'd like to thank Recursal / Featherless for sponsoring the compute for this train, Featherless has been hosting our Magnum models since the first 72 B and has given thousands of people access to our models and helped us grow.
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We would also like to thank all members of Anthracite who made this finetune possible.
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Datasets
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anthracite-org/c2_logs_32k_llama3_qwen2_v1.2_no_system
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anthracite-org/kalo-opus-instruct-22k-no-refusal-no-system
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anthracite-org/kalo-opus-instruct-3k-filtered-no-system
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anthracite-org/nopm_claude_writing_fixed
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anthracite-org/kalo_opus_misc_240827_no_system
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anthracite-org/kalo_misc_part2_no_system
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Training
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The training was done for 2 epochs. We used 8xH100s GPUs graciously provided by Recursal AI / Featherless AI for the full-parameter fine-tuning of the model.
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---
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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---
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language:
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- en
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license: apache-2.0
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library_name: transformers
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tags:
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- chat
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- llama-cpp
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- gguf-my-repo
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pipeline_tag: text-generation
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base_model: anthracite-org/magnum-v4-12b
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model-index:
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- name: magnum-v4-12b
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: IFEval (0-Shot)
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type: HuggingFaceH4/ifeval
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args:
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num_few_shot: 0
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metrics:
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- type: inst_level_strict_acc and prompt_level_strict_acc
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value: 33.93
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name: strict accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-12b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BBH (3-Shot)
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type: BBH
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args:
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num_few_shot: 3
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metrics:
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- type: acc_norm
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value: 30.5
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-12b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MATH Lvl 5 (4-Shot)
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type: hendrycks/competition_math
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args:
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num_few_shot: 4
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metrics:
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- type: exact_match
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value: 9.82
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name: exact match
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-12b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GPQA (0-shot)
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type: Idavidrein/gpqa
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 6.15
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-12b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MuSR (0-shot)
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type: TAUR-Lab/MuSR
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args:
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num_few_shot: 0
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metrics:
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- type: acc_norm
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value: 10.36
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name: acc_norm
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-12b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU-PRO (5-shot)
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type: TIGER-Lab/MMLU-Pro
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 28.93
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name: accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=anthracite-org/magnum-v4-12b
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name: Open LLM Leaderboard
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---
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# Triangle104/magnum-v4-12b-Q4_K_S-GGUF
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This model was converted to GGUF format from [`anthracite-org/magnum-v4-12b`](https://huggingface.co/anthracite-org/magnum-v4-12b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/anthracite-org/magnum-v4-12b) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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