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llm-agents_tora-code-7b-v1.0-GGUF

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  1. .gitattributes +12 -0
  2. README.md +123 -0
  3. tora-code-7b-v1.0-Q2_K.gguf +3 -0
  4. tora-code-7b-v1.0-Q3_K_L.gguf +3 -0
  5. tora-code-7b-v1.0-Q3_K_M.gguf +3 -0
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  12. tora-code-7b-v1.0-Q5_K_S.gguf +3 -0
  13. tora-code-7b-v1.0-Q6_K.gguf +3 -0
  14. tora-code-7b-v1.0-Q8_0.gguf +3 -0
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@@ -33,3 +33,15 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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+ tora-code-7b-v1.0-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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+ tora-code-7b-v1.0-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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+ tora-code-7b-v1.0-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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+ tora-code-7b-v1.0-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ license: llama2
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+ datasets:
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+ - gsm8k
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+ - competition_math
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+ language:
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+ - en
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+ metrics:
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+ - exact_match
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ tags:
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+ - code
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+ - math
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+ - TensorBlock
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+ - GGUF
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+ base_model: llm-agents/tora-code-7b-v1.0
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+ ---
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+
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+ <div style="width: auto; margin-left: auto; margin-right: auto">
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+ <img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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+ </div>
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+ <div style="display: flex; justify-content: space-between; width: 100%;">
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+ <div style="display: flex; flex-direction: column; align-items: flex-start;">
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+ <p style="margin-top: 0.5em; margin-bottom: 0em;">
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+ 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>
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+ </p>
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+ </div>
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+ </div>
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+
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+ ## llm-agents/tora-code-7b-v1.0 - GGUF
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+
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+ This repo contains GGUF format model files for [llm-agents/tora-code-7b-v1.0](https://huggingface.co/llm-agents/tora-code-7b-v1.0).
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+
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+ The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5165](https://github.com/ggml-org/llama.cpp/commit/1d735c0b4fa0551c51c2f4ac888dd9a01f447985).
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+
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+ ## Our projects
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+ <table border="1" cellspacing="0" cellpadding="10">
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+ <tr>
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+ <th style="font-size: 25px;">Awesome MCP Servers</th>
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+ <th style="font-size: 25px;">TensorBlock Studio</th>
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+ </tr>
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+ <tr>
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+ <th><img src="https://imgur.com/2Xov7B7.jpeg" alt="Project A" width="450"/></th>
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+ <th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Project B" width="450"/></th>
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+ </tr>
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+ <tr>
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+ <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
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+ <th>A lightweight, open, and extensible multi-LLM interaction studio.</th>
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+ </tr>
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+ <tr>
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+ <th>
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+ <a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style="
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+ display: inline-block;
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+ padding: 8px 16px;
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+ background-color: #FF7F50;
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+ color: white;
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+ text-decoration: none;
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+ border-radius: 6px;
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+ font-weight: bold;
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+ font-family: sans-serif;
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+ ">👀 See what we built 👀</a>
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+ </th>
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+ <th>
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+ <a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style="
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+ display: inline-block;
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+ padding: 8px 16px;
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+ background-color: #FF7F50;
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+ color: white;
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+ text-decoration: none;
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+ border-radius: 6px;
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+ font-weight: bold;
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+ font-family: sans-serif;
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+ ">👀 See what we built 👀</a>
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+ </th>
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+ </tr>
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+ </table>
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+
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+ ## Prompt template
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+
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+ ```
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+
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+ ```
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+
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+ ## Model file specification
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+
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+ | Filename | Quant type | File Size | Description |
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+ | -------- | ---------- | --------- | ----------- |
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+ | [tora-code-7b-v1.0-Q2_K.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q2_K.gguf) | Q2_K | 2.533 GB | smallest, significant quality loss - not recommended for most purposes |
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+ | [tora-code-7b-v1.0-Q3_K_S.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q3_K_S.gguf) | Q3_K_S | 2.948 GB | very small, high quality loss |
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+ | [tora-code-7b-v1.0-Q3_K_M.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q3_K_M.gguf) | Q3_K_M | 3.298 GB | very small, high quality loss |
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+ | [tora-code-7b-v1.0-Q3_K_L.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q3_K_L.gguf) | Q3_K_L | 3.597 GB | small, substantial quality loss |
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+ | [tora-code-7b-v1.0-Q4_0.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q4_0.gguf) | Q4_0 | 3.826 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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+ | [tora-code-7b-v1.0-Q4_K_S.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q4_K_S.gguf) | Q4_K_S | 3.857 GB | small, greater quality loss |
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+ | [tora-code-7b-v1.0-Q4_K_M.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q4_K_M.gguf) | Q4_K_M | 4.081 GB | medium, balanced quality - recommended |
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+ | [tora-code-7b-v1.0-Q5_0.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q5_0.gguf) | Q5_0 | 4.652 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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+ | [tora-code-7b-v1.0-Q5_K_S.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q5_K_S.gguf) | Q5_K_S | 4.652 GB | large, low quality loss - recommended |
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+ | [tora-code-7b-v1.0-Q5_K_M.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q5_K_M.gguf) | Q5_K_M | 4.783 GB | large, very low quality loss - recommended |
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+ | [tora-code-7b-v1.0-Q6_K.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q6_K.gguf) | Q6_K | 5.529 GB | very large, extremely low quality loss |
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+ | [tora-code-7b-v1.0-Q8_0.gguf](https://huggingface.co/tensorblock/llm-agents_tora-code-7b-v1.0-GGUF/blob/main/tora-code-7b-v1.0-Q8_0.gguf) | Q8_0 | 7.161 GB | very large, extremely low quality loss - not recommended |
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+
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+
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+ ## Downloading instruction
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+
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+ ### Command line
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+
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+ Firstly, install Huggingface Client
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+
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+ ```shell
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+ pip install -U "huggingface_hub[cli]"
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+ ```
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+
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+ Then, downoad the individual model file the a local directory
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+
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+ ```shell
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+ huggingface-cli download tensorblock/llm-agents_tora-code-7b-v1.0-GGUF --include "tora-code-7b-v1.0-Q2_K.gguf" --local-dir MY_LOCAL_DIR
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+ ```
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+
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+ If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
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+
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+ ```shell
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+ huggingface-cli download tensorblock/llm-agents_tora-code-7b-v1.0-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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+ ```
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