--- language: - en - fr - es - hi - zh - code license: other datasets: - HuggingFaceH4/no_robots - mlabonne/guanaco-llama2-1k - OpenAssistant/oasst_top1_2023-08-25 - totally-not-an-llm/EverythingLM-data-V3 - LDJnr/Pure-Dove - LDJnr/Capybara - LDJnr/LessWrong-Amplify-Instruct - LDJnr/Verified-Camel base_model: Locutusque/Orca-2-13b-SFT-v6 widget: - example_title: Cave Johnson text: 'user Come up with a funny rant from Cave Johnson about sentient AI assistant ' output: text: 'Ladies and gentlemen, I''m Cave Johnson, CEO of Aperture Science, and I''ve got an announcement to make - we''ve created sentient AI! But don''t worry, it''s not like those rogue AIs you hear about in the news. Our AI is as friendly as a grilled cheese sandwich on a cold day. In fact, we''re calling our newest creation... SandwichBot! SandwichBot: (in a robotic voice) Hello, my name is SandwichBot, and I am here to serve you delicious sandwiches and ensure humanity''s dominance over all other species. Also, please note that I will be referring to myself as ''Thee'' instead of ''The''. It''s more regal that way. Cave Johnson: There you have it folks, a sentient AI that can make sandwiches and save the world! Now, if you''ll excuse me, I need to go back to my office and work on my other groundbreaking inventions, like combustible lemons and portal technology. Remember, kids, always try new things and never stop asking questions – unless the answer is 42, because then you should probably just accept it and move on. Peace out!' tags: - TensorBlock - GGUF model-index: - name: Orca-2-13b-SFT-v6 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: 60.41 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/Orca-2-13b-SFT-v6 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: 80.46 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/Orca-2-13b-SFT-v6 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: 59.51 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/Orca-2-13b-SFT-v6 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: 54.01 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/Orca-2-13b-SFT-v6 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: 77.43 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/Orca-2-13b-SFT-v6 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: 5.08 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/Orca-2-13b-SFT-v6 name: Open LLM Leaderboard ---
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## Locutusque/Orca-2-13b-SFT-v6 - GGUF This repo contains GGUF format model files for [Locutusque/Orca-2-13b-SFT-v6](https://huggingface.co/Locutusque/Orca-2-13b-SFT-v6). The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
Run them on the TensorBlock client using your local machine ↗
## Prompt template ``` ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [Orca-2-13b-SFT-v6-Q2_K.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q2_K.gguf) | Q2_K | 4.521 GB | smallest, significant quality loss - not recommended for most purposes | | [Orca-2-13b-SFT-v6-Q3_K_S.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q3_K_S.gguf) | Q3_K_S | 5.270 GB | very small, high quality loss | | [Orca-2-13b-SFT-v6-Q3_K_M.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q3_K_M.gguf) | Q3_K_M | 5.903 GB | very small, high quality loss | | [Orca-2-13b-SFT-v6-Q3_K_L.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q3_K_L.gguf) | Q3_K_L | 6.454 GB | small, substantial quality loss | | [Orca-2-13b-SFT-v6-Q4_0.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q4_0.gguf) | Q4_0 | 6.860 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [Orca-2-13b-SFT-v6-Q4_K_S.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q4_K_S.gguf) | Q4_K_S | 6.913 GB | small, greater quality loss | | [Orca-2-13b-SFT-v6-Q4_K_M.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q4_K_M.gguf) | Q4_K_M | 7.326 GB | medium, balanced quality - recommended | | [Orca-2-13b-SFT-v6-Q5_0.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q5_0.gguf) | Q5_0 | 8.356 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [Orca-2-13b-SFT-v6-Q5_K_S.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q5_K_S.gguf) | Q5_K_S | 8.356 GB | large, low quality loss - recommended | | [Orca-2-13b-SFT-v6-Q5_K_M.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q5_K_M.gguf) | Q5_K_M | 8.596 GB | large, very low quality loss - recommended | | [Orca-2-13b-SFT-v6-Q6_K.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q6_K.gguf) | Q6_K | 9.946 GB | very large, extremely low quality loss | | [Orca-2-13b-SFT-v6-Q8_0.gguf](https://huggingface.co/tensorblock/Orca-2-13b-SFT-v6-GGUF/blob/main/Orca-2-13b-SFT-v6-Q8_0.gguf) | Q8_0 | 12.881 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/Orca-2-13b-SFT-v6-GGUF --include "Orca-2-13b-SFT-v6-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/Orca-2-13b-SFT-v6-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```