tensorblock
/

Qwen2.5-32B-Instruct-GGUF

@@ -1,121 +1,133 @@
----
-license: apache-2.0
-license_link: https://huggingface.co/Qwen/Qwen2.5-32B-Instruct/blob/main/LICENSE
-language:
-- en
-pipeline_tag: text-generation
-base_model: Qwen/Qwen2.5-32B-Instruct
-tags:
-- chat
-- TensorBlock
-- GGUF
-library_name: transformers
----
-<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>
-## Qwen/Qwen2.5-32B-Instruct - GGUF
-This repo contains GGUF format model files for [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).
-The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit ec7f3ac](https://github.com/ggerganov/llama.cpp/commit/ec7f3ac9ab33e46b136eb5ab6a76c4d81f57c7f1).
-## Our projects
-<table border="1" cellspacing="0" cellpadding="10">
-<tr>
-  <th style="font-size: 25px;">Awesome MCP Servers</th>
-  <th style="font-size: 25px;">TensorBlock Studio</th>
-</tr>
-  <tr>
-    <th><img src="https://imgur.com/2Xov7B7.jpeg" alt="Project A" width="450"/></th>
-    <th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Project B" width="450"/></th>
-  </tr>
-  <tr>
-    <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
-    <th>A lightweight, open, and extensible multi-LLM interaction studio.</th>
-  </tr>
-<tr>
-  <th>
-    <a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style="
-      display: inline-block;
-      padding: 8px 16px;
-      background-color: #FF7F50;
-      color: white;
-      text-decoration: none;
-      border-radius: 6px;
-      font-weight: bold;
-      font-family: sans-serif;
-    ">👀 See what we built 👀</a>
-  </th>
-  <th>
-    <a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style="
-      display: inline-block;
-      padding: 8px 16px;
-      background-color: #FF7F50;
-      color: white;
-      text-decoration: none;
-      border-radius: 6px;
-      font-weight: bold;
-      font-family: sans-serif;
-    ">👀 See what we built 👀</a>
-  </th>
-</tr>
-</table>
-## 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 |
-| -------- | ---------- | --------- | ----------- |
-| [Qwen2.5-32B-Instruct-Q2_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q2_K.gguf) | Q2_K | 12.313 GB | smallest, significant quality loss - not recommended for most purposes |
-| [Qwen2.5-32B-Instruct-Q3_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q3_K_S.gguf) | Q3_K_S | 14.392 GB | very small, high quality loss |
-| [Qwen2.5-32B-Instruct-Q3_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q3_K_M.gguf) | Q3_K_M | 15.935 GB | very small, high quality loss |
-| [Qwen2.5-32B-Instruct-Q3_K_L.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q3_K_L.gguf) | Q3_K_L | 17.247 GB | small, substantial quality loss |
-| [Qwen2.5-32B-Instruct-Q4_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q4_0.gguf) | Q4_0 | 18.640 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
-| [Qwen2.5-32B-Instruct-Q4_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q4_K_S.gguf) | Q4_K_S | 18.784 GB | small, greater quality loss |
-| [Qwen2.5-32B-Instruct-Q4_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q4_K_M.gguf) | Q4_K_M | 19.851 GB | medium, balanced quality - recommended |
-| [Qwen2.5-32B-Instruct-Q5_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q5_0.gguf) | Q5_0 | 22.638 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
-| [Qwen2.5-32B-Instruct-Q5_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q5_K_S.gguf) | Q5_K_S | 22.638 GB | large, low quality loss - recommended |
-| [Qwen2.5-32B-Instruct-Q5_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q5_K_M.gguf) | Q5_K_M | 23.262 GB | large, very low quality loss - recommended |
-| [Qwen2.5-32B-Instruct-Q6_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q6_K.gguf) | Q6_K | 26.886 GB | very large, extremely low quality loss |
-| [Qwen2.5-32B-Instruct-Q8_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q8_0.gguf) | Q8_0 | 34.821 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/Qwen2.5-32B-Instruct-GGUF --include "Qwen2.5-32B-Instruct-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/Qwen2.5-32B-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
-```

+---
+license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen2.5-32B-Instruct/blob/main/LICENSE
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+pipeline_tag: text-generation
+base_model: Qwen/Qwen2.5-32B-Instruct
+tags:
+- chat
+- TensorBlock
+- GGUF
+library_name: transformers
+---
+<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>
+## Qwen/Qwen2.5-32B-Instruct - GGUF
+This repo contains GGUF format model files for [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).
+The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit ec7f3ac](https://github.com/ggerganov/llama.cpp/commit/ec7f3ac9ab33e46b136eb5ab6a76c4d81f57c7f1).
+## Our projects
+<table border="1" cellspacing="0" cellpadding="10">
+<tr>
+  <th style="font-size: 25px;">Awesome MCP Servers</th>
+  <th style="font-size: 25px;">TensorBlock Studio</th>
+</tr>
+  <tr>
+    <th><img src="https://imgur.com/2Xov7B7.jpeg" alt="Project A" width="450"/></th>
+    <th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Project B" width="450"/></th>
+  </tr>
+  <tr>
+    <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
+    <th>A lightweight, open, and extensible multi-LLM interaction studio.</th>
+  </tr>
+<tr>
+  <th>
+    <a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style="
+      display: inline-block;
+      padding: 8px 16px;
+      background-color: #FF7F50;
+      color: white;
+      text-decoration: none;
+      border-radius: 6px;
+      font-weight: bold;
+      font-family: sans-serif;
+    ">👀 See what we built 👀</a>
+  </th>
+  <th>
+    <a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style="
+      display: inline-block;
+      padding: 8px 16px;
+      background-color: #FF7F50;
+      color: white;
+      text-decoration: none;
+      border-radius: 6px;
+      font-weight: bold;
+      font-family: sans-serif;
+    ">👀 See what we built 👀</a>
+  </th>
+</tr>
+</table>
+## 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 |
+| -------- | ---------- | --------- | ----------- |
+| [Qwen2.5-32B-Instruct-Q2_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q2_K.gguf) | Q2_K | 12.313 GB | smallest, significant quality loss - not recommended for most purposes |
+| [Qwen2.5-32B-Instruct-Q3_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q3_K_S.gguf) | Q3_K_S | 14.392 GB | very small, high quality loss |
+| [Qwen2.5-32B-Instruct-Q3_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q3_K_M.gguf) | Q3_K_M | 15.935 GB | very small, high quality loss |
+| [Qwen2.5-32B-Instruct-Q3_K_L.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q3_K_L.gguf) | Q3_K_L | 17.247 GB | small, substantial quality loss |
+| [Qwen2.5-32B-Instruct-Q4_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q4_0.gguf) | Q4_0 | 18.640 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [Qwen2.5-32B-Instruct-Q4_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q4_K_S.gguf) | Q4_K_S | 18.784 GB | small, greater quality loss |
+| [Qwen2.5-32B-Instruct-Q4_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q4_K_M.gguf) | Q4_K_M | 19.851 GB | medium, balanced quality - recommended |
+| [Qwen2.5-32B-Instruct-Q5_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q5_0.gguf) | Q5_0 | 22.638 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [Qwen2.5-32B-Instruct-Q5_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q5_K_S.gguf) | Q5_K_S | 22.638 GB | large, low quality loss - recommended |
+| [Qwen2.5-32B-Instruct-Q5_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q5_K_M.gguf) | Q5_K_M | 23.262 GB | large, very low quality loss - recommended |
+| [Qwen2.5-32B-Instruct-Q6_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q6_K.gguf) | Q6_K | 26.886 GB | very large, extremely low quality loss |
+| [Qwen2.5-32B-Instruct-Q8_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-32B-Instruct-GGUF/blob/main/Qwen2.5-32B-Instruct-Q8_0.gguf) | Q8_0 | 34.821 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/Qwen2.5-32B-Instruct-GGUF --include "Qwen2.5-32B-Instruct-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/Qwen2.5-32B-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
+```