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  12. Qwen2.5-Coder-1.5B-Instruct-Q8_0.gguf +2 -2
  13. README.md +18 -25
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README.md CHANGED
@@ -1,17 +1,12 @@
1
  ---
2
- license: apache-2.0
3
- license_link: https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct/blob/main/LICENSE
4
  language:
5
  - en
6
- base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
7
- pipeline_tag: text-generation
8
  library_name: transformers
 
9
  tags:
10
- - code
11
- - codeqwen
12
- - chat
13
- - qwen
14
- - qwen-coder
15
  - TensorBlock
16
  - GGUF
17
  ---
@@ -27,13 +22,12 @@ tags:
27
  </div>
28
  </div>
29
 
30
- ## Qwen/Qwen2.5-Coder-1.5B-Instruct - GGUF
31
 
32
- This repo contains GGUF format model files for [Qwen/Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct).
33
 
34
  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).
35
 
36
-
37
  <div style="text-align: left; margin: 20px 0;">
38
  <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
39
  Run them on the TensorBlock client using your local machine ↗
@@ -42,7 +36,6 @@ The files were quantized using machines provided by [TensorBlock](https://tensor
42
 
43
  ## Prompt template
44
 
45
-
46
  ```
47
  <|im_start|>system
48
  {system_prompt}<|im_end|>
@@ -55,18 +48,18 @@ The files were quantized using machines provided by [TensorBlock](https://tensor
55
 
56
  | Filename | Quant type | File Size | Description |
57
  | -------- | ---------- | --------- | ----------- |
58
- | [Qwen2.5-Coder-1.5B-Instruct-Q2_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q2_K.gguf) | Q2_K | 0.630 GB | smallest, significant quality loss - not recommended for most purposes |
59
- | [Qwen2.5-Coder-1.5B-Instruct-Q3_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q3_K_S.gguf) | Q3_K_S | 0.709 GB | very small, high quality loss |
60
- | [Qwen2.5-Coder-1.5B-Instruct-Q3_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q3_K_M.gguf) | Q3_K_M | 0.768 GB | very small, high quality loss |
61
- | [Qwen2.5-Coder-1.5B-Instruct-Q3_K_L.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q3_K_L.gguf) | Q3_K_L | 0.820 GB | small, substantial quality loss |
62
- | [Qwen2.5-Coder-1.5B-Instruct-Q4_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q4_0.gguf) | Q4_0 | 0.871 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
63
- | [Qwen2.5-Coder-1.5B-Instruct-Q4_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q4_K_S.gguf) | Q4_K_S | 0.876 GB | small, greater quality loss |
64
- | [Qwen2.5-Coder-1.5B-Instruct-Q4_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q4_K_M.gguf) | Q4_K_M | 0.918 GB | medium, balanced quality - recommended |
65
- | [Qwen2.5-Coder-1.5B-Instruct-Q5_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q5_0.gguf) | Q5_0 | 1.023 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
66
- | [Qwen2.5-Coder-1.5B-Instruct-Q5_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q5_K_S.gguf) | Q5_K_S | 1.023 GB | large, low quality loss - recommended |
67
- | [Qwen2.5-Coder-1.5B-Instruct-Q5_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q5_K_M.gguf) | Q5_K_M | 1.048 GB | large, very low quality loss - recommended |
68
- | [Qwen2.5-Coder-1.5B-Instruct-Q6_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q6_K.gguf) | Q6_K | 1.185 GB | very large, extremely low quality loss |
69
- | [Qwen2.5-Coder-1.5B-Instruct-Q8_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q8_0.gguf) | Q8_0 | 1.533 GB | very large, extremely low quality loss - not recommended |
70
 
71
 
72
  ## Downloading instruction
 
1
  ---
2
+ base_model: unsloth/Qwen2.5-Coder-1.5B-Instruct
 
3
  language:
4
  - en
 
 
5
  library_name: transformers
6
+ license: apache-2.0
7
  tags:
8
+ - unsloth
9
+ - transformers
 
 
 
10
  - TensorBlock
11
  - GGUF
12
  ---
 
22
  </div>
23
  </div>
24
 
25
+ ## unsloth/Qwen2.5-Coder-1.5B-Instruct - GGUF
26
 
27
+ This repo contains GGUF format model files for [unsloth/Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/unsloth/Qwen2.5-Coder-1.5B-Instruct).
28
 
29
  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).
30
 
 
31
  <div style="text-align: left; margin: 20px 0;">
32
  <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
33
  Run them on the TensorBlock client using your local machine ↗
 
36
 
37
  ## Prompt template
38
 
 
39
  ```
40
  <|im_start|>system
41
  {system_prompt}<|im_end|>
 
48
 
49
  | Filename | Quant type | File Size | Description |
50
  | -------- | ---------- | --------- | ----------- |
51
+ | [Qwen2.5-Coder-1.5B-Instruct-Q2_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q2_K.gguf) | Q2_K | 0.676 GB | smallest, significant quality loss - not recommended for most purposes |
52
+ | [Qwen2.5-Coder-1.5B-Instruct-Q3_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q3_K_S.gguf) | Q3_K_S | 0.761 GB | very small, high quality loss |
53
+ | [Qwen2.5-Coder-1.5B-Instruct-Q3_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q3_K_M.gguf) | Q3_K_M | 0.824 GB | very small, high quality loss |
54
+ | [Qwen2.5-Coder-1.5B-Instruct-Q3_K_L.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q3_K_L.gguf) | Q3_K_L | 0.880 GB | small, substantial quality loss |
55
+ | [Qwen2.5-Coder-1.5B-Instruct-Q4_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q4_0.gguf) | Q4_0 | 0.935 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
56
+ | [Qwen2.5-Coder-1.5B-Instruct-Q4_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q4_K_S.gguf) | Q4_K_S | 0.940 GB | small, greater quality loss |
57
+ | [Qwen2.5-Coder-1.5B-Instruct-Q4_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q4_K_M.gguf) | Q4_K_M | 0.986 GB | medium, balanced quality - recommended |
58
+ | [Qwen2.5-Coder-1.5B-Instruct-Q5_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q5_0.gguf) | Q5_0 | 1.099 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
59
+ | [Qwen2.5-Coder-1.5B-Instruct-Q5_K_S.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q5_K_S.gguf) | Q5_K_S | 1.099 GB | large, low quality loss - recommended |
60
+ | [Qwen2.5-Coder-1.5B-Instruct-Q5_K_M.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q5_K_M.gguf) | Q5_K_M | 1.125 GB | large, very low quality loss - recommended |
61
+ | [Qwen2.5-Coder-1.5B-Instruct-Q6_K.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q6_K.gguf) | Q6_K | 1.273 GB | very large, extremely low quality loss |
62
+ | [Qwen2.5-Coder-1.5B-Instruct-Q8_0.gguf](https://huggingface.co/tensorblock/Qwen2.5-Coder-1.5B-Instruct-GGUF/blob/main/Qwen2.5-Coder-1.5B-Instruct-Q8_0.gguf) | Q8_0 | 1.647 GB | very large, extremely low quality loss - not recommended |
63
 
64
 
65
  ## Downloading instruction