--- language: - en license: llama3 library_name: transformers tags: - axolotl - finetune - dpo - facebook - meta - pytorch - llama - llama-3 - chatml - TensorBlock - GGUF base_model: MaziyarPanahi/calme-2.3-llama3-70b datasets: - MaziyarPanahi/truthy-dpo-v0.1-axolotl pipeline_tag: text-generation license_name: llama3 license_link: LICENSE inference: false model_creator: MaziyarPanahi quantized_by: MaziyarPanahi model-index: - name: calme-2.3-llama3-70b results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 72.35 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 86 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 80.47 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 63.45 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 82.95 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 87.19 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b name: Open LLM Leaderboard ---
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## MaziyarPanahi/calme-2.3-llama3-70b - GGUF This repo contains GGUF format model files for [MaziyarPanahi/calme-2.3-llama3-70b](https://huggingface.co/MaziyarPanahi/calme-2.3-llama3-70b). The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
Run them on the TensorBlock client using your local machine ↗
## Prompt template ``` <|im_start|>system {system_prompt}<|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [calme-2.3-llama3-70b-Q2_K.gguf](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q2_K.gguf) | Q2_K | 26.375 GB | smallest, significant quality loss - not recommended for most purposes | | [calme-2.3-llama3-70b-Q3_K_S.gguf](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q3_K_S.gguf) | Q3_K_S | 30.912 GB | very small, high quality loss | | [calme-2.3-llama3-70b-Q3_K_M.gguf](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q3_K_M.gguf) | Q3_K_M | 34.268 GB | very small, high quality loss | | [calme-2.3-llama3-70b-Q3_K_L.gguf](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q3_K_L.gguf) | Q3_K_L | 37.141 GB | small, substantial quality loss | | [calme-2.3-llama3-70b-Q4_0.gguf](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q4_0.gguf) | Q4_0 | 39.970 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [calme-2.3-llama3-70b-Q4_K_S.gguf](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q4_K_S.gguf) | Q4_K_S | 40.347 GB | small, greater quality loss | | [calme-2.3-llama3-70b-Q4_K_M.gguf](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q4_K_M.gguf) | Q4_K_M | 42.520 GB | medium, balanced quality - recommended | | [calme-2.3-llama3-70b-Q5_0.gguf](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q5_0.gguf) | Q5_0 | 48.657 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [calme-2.3-llama3-70b-Q5_K_S.gguf](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q5_K_S.gguf) | Q5_K_S | 48.657 GB | large, low quality loss - recommended | | [calme-2.3-llama3-70b-Q5_K_M.gguf](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q5_K_M.gguf) | Q5_K_M | 49.950 GB | large, very low quality loss - recommended | | [calme-2.3-llama3-70b-Q8_0](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q8_0) | Q6_K | 74.975 GB | very large, extremely low quality loss | | [calme-2.3-llama3-70b-Q6_K](https://huggingface.co/tensorblock/calme-2.3-llama3-70b-GGUF/blob/main/calme-2.3-llama3-70b-Q6_K) | Q8_0 | 57.888 GB | very large, extremely low quality loss - not recommended | ## Downloading instruction ### Command line Firstly, install Huggingface Client ```shell pip install -U "huggingface_hub[cli]" ``` Then, downoad the individual model file the a local directory ```shell huggingface-cli download tensorblock/calme-2.3-llama3-70b-GGUF --include "calme-2.3-llama3-70b-Q2_K.gguf" --local-dir MY_LOCAL_DIR ``` If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: ```shell huggingface-cli download tensorblock/calme-2.3-llama3-70b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```