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.gitattributes

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README.md

@@ -0,0 +1,214 @@
+---
+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
+---
+
+<div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+</div>
+<div style="display: flex; justify-content: space-between; width: 100%;">
+    <div style="display: flex; flex-direction: column; align-items: flex-start;">
+        <p style="margin-top: 0.5em; margin-bottom: 0em;">
+            Feedback and support: TensorBlock's  <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
+        </p>
+    </div>
+</div>
+
+## 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).
+
+## 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/tree/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/tree/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/tree/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/tree/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/tree/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/tree/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/tree/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/tree/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/tree/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/tree/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/tree/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/tree/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'
+```