Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
- README.md +116 -0
- finetune-llama-3.2-1b-mbpp-Q2_K.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q3_K_L.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q3_K_M.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q3_K_S.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q4_0.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q4_K_M.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q4_K_S.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q5_0.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q5_K_M.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q5_K_S.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q6_K.gguf +3 -0
- finetune-llama-3.2-1b-mbpp-Q8_0.gguf +3 -0
.gitattributes
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finetune-llama-3.2-1b-mbpp-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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finetune-llama-3.2-1b-mbpp-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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+
---
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+
library_name: transformers
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tags:
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- TensorBlock
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- GGUF
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base_model: ALIN-LLM/finetune-llama-3.2-1b-mbpp
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---
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8 |
+
|
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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;">
|
11 |
+
</div>
|
12 |
+
<div style="display: flex; justify-content: space-between; width: 100%;">
|
13 |
+
<div style="display: flex; flex-direction: column; align-items: flex-start;">
|
14 |
+
<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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## ALIN-LLM/finetune-llama-3.2-1b-mbpp - GGUF
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This repo contains GGUF format model files for [ALIN-LLM/finetune-llama-3.2-1b-mbpp](https://huggingface.co/ALIN-LLM/finetune-llama-3.2-1b-mbpp).
|
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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
|
27 |
+
<table border="1" cellspacing="0" cellpadding="10">
|
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+
<tr>
|
29 |
+
<th style="font-size: 25px;">Awesome MCP Servers</th>
|
30 |
+
<th style="font-size: 25px;">TensorBlock Studio</th>
|
31 |
+
</tr>
|
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+
<tr>
|
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+
<th><img src="https://imgur.com/2Xov7B7.jpeg" alt="Project A" width="450"/></th>
|
34 |
+
<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;
|
44 |
+
padding: 8px 16px;
|
45 |
+
background-color: #FF7F50;
|
46 |
+
color: white;
|
47 |
+
text-decoration: none;
|
48 |
+
border-radius: 6px;
|
49 |
+
font-weight: bold;
|
50 |
+
font-family: sans-serif;
|
51 |
+
">👀 See what we built 👀</a>
|
52 |
+
</th>
|
53 |
+
<th>
|
54 |
+
<a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style="
|
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+
display: inline-block;
|
56 |
+
padding: 8px 16px;
|
57 |
+
background-color: #FF7F50;
|
58 |
+
color: white;
|
59 |
+
text-decoration: none;
|
60 |
+
border-radius: 6px;
|
61 |
+
font-weight: bold;
|
62 |
+
font-family: sans-serif;
|
63 |
+
">👀 See what we built 👀</a>
|
64 |
+
</th>
|
65 |
+
</tr>
|
66 |
+
</table>
|
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+
|
68 |
+
## Prompt template
|
69 |
+
|
70 |
+
```
|
71 |
+
<|system|>
|
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+
{system_prompt}
|
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+
<|user|>
|
74 |
+
{prompt}
|
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+
<|assistant|>
|
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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 |
|
81 |
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| -------- | ---------- | --------- | ----------- |
|
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+
| [finetune-llama-3.2-1b-mbpp-Q2_K.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q2_K.gguf) | Q2_K | 0.581 GB | smallest, significant quality loss - not recommended for most purposes |
|
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+
| [finetune-llama-3.2-1b-mbpp-Q3_K_S.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q3_K_S.gguf) | Q3_K_S | 0.642 GB | very small, high quality loss |
|
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+
| [finetune-llama-3.2-1b-mbpp-Q3_K_M.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q3_K_M.gguf) | Q3_K_M | 0.691 GB | very small, high quality loss |
|
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+
| [finetune-llama-3.2-1b-mbpp-Q3_K_L.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q3_K_L.gguf) | Q3_K_L | 0.733 GB | small, substantial quality loss |
|
86 |
+
| [finetune-llama-3.2-1b-mbpp-Q4_0.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q4_0.gguf) | Q4_0 | 0.771 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
87 |
+
| [finetune-llama-3.2-1b-mbpp-Q4_K_S.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q4_K_S.gguf) | Q4_K_S | 0.776 GB | small, greater quality loss |
|
88 |
+
| [finetune-llama-3.2-1b-mbpp-Q4_K_M.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q4_K_M.gguf) | Q4_K_M | 0.808 GB | medium, balanced quality - recommended |
|
89 |
+
| [finetune-llama-3.2-1b-mbpp-Q5_0.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q5_0.gguf) | Q5_0 | 0.893 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
90 |
+
| [finetune-llama-3.2-1b-mbpp-Q5_K_S.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q5_K_S.gguf) | Q5_K_S | 0.893 GB | large, low quality loss - recommended |
|
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+
| [finetune-llama-3.2-1b-mbpp-Q5_K_M.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q5_K_M.gguf) | Q5_K_M | 0.911 GB | large, very low quality loss - recommended |
|
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+
| [finetune-llama-3.2-1b-mbpp-Q6_K.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q6_K.gguf) | Q6_K | 1.022 GB | very large, extremely low quality loss |
|
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+
| [finetune-llama-3.2-1b-mbpp-Q8_0.gguf](https://huggingface.co/tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF/blob/main/finetune-llama-3.2-1b-mbpp-Q8_0.gguf) | Q8_0 | 1.321 GB | very large, extremely low quality loss - not recommended |
|
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+
|
95 |
+
|
96 |
+
## Downloading instruction
|
97 |
+
|
98 |
+
### Command line
|
99 |
+
|
100 |
+
Firstly, install Huggingface Client
|
101 |
+
|
102 |
+
```shell
|
103 |
+
pip install -U "huggingface_hub[cli]"
|
104 |
+
```
|
105 |
+
|
106 |
+
Then, downoad the individual model file the a local directory
|
107 |
+
|
108 |
+
```shell
|
109 |
+
huggingface-cli download tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF --include "finetune-llama-3.2-1b-mbpp-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
110 |
+
```
|
111 |
+
|
112 |
+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
113 |
+
|
114 |
+
```shell
|
115 |
+
huggingface-cli download tensorblock/ALIN-LLM_finetune-llama-3.2-1b-mbpp-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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```
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finetune-llama-3.2-1b-mbpp-Q2_K.gguf
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