Update README.md
Browse files
README.md
CHANGED
|
@@ -91,8 +91,16 @@ This repo contains GGUF format model files for [ibm-granite/granite-8b-code-inst
|
|
| 91 |
|
| 92 |
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).
|
| 93 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 94 |
## Prompt template
|
| 95 |
|
|
|
|
| 96 |
```
|
| 97 |
System:
|
| 98 |
{system_prompt}
|
|
@@ -107,18 +115,18 @@ Answer:
|
|
| 107 |
|
| 108 |
| Filename | Quant type | File Size | Description |
|
| 109 |
| -------- | ---------- | --------- | ----------- |
|
| 110 |
-
| [granite-8b-code-instruct-128k-Q2_K.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 111 |
-
| [granite-8b-code-instruct-128k-Q3_K_S.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 112 |
-
| [granite-8b-code-instruct-128k-Q3_K_M.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 113 |
-
| [granite-8b-code-instruct-128k-Q3_K_L.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 114 |
-
| [granite-8b-code-instruct-128k-Q4_0.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 115 |
-
| [granite-8b-code-instruct-128k-Q4_K_S.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 116 |
-
| [granite-8b-code-instruct-128k-Q4_K_M.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 117 |
-
| [granite-8b-code-instruct-128k-Q5_0.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 118 |
-
| [granite-8b-code-instruct-128k-Q5_K_S.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 119 |
-
| [granite-8b-code-instruct-128k-Q5_K_M.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 120 |
-
| [granite-8b-code-instruct-128k-Q6_K.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 121 |
-
| [granite-8b-code-instruct-128k-Q8_0.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/
|
| 122 |
|
| 123 |
|
| 124 |
## Downloading instruction
|
|
|
|
| 91 |
|
| 92 |
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).
|
| 93 |
|
| 94 |
+
|
| 95 |
+
<div style="text-align: left; margin: 20px 0;">
|
| 96 |
+
<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;">
|
| 97 |
+
Run them on the TensorBlock client using your local machine ↗
|
| 98 |
+
</a>
|
| 99 |
+
</div>
|
| 100 |
+
|
| 101 |
## Prompt template
|
| 102 |
|
| 103 |
+
|
| 104 |
```
|
| 105 |
System:
|
| 106 |
{system_prompt}
|
|
|
|
| 115 |
|
| 116 |
| Filename | Quant type | File Size | Description |
|
| 117 |
| -------- | ---------- | --------- | ----------- |
|
| 118 |
+
| [granite-8b-code-instruct-128k-Q2_K.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q2_K.gguf) | Q2_K | 2.852 GB | smallest, significant quality loss - not recommended for most purposes |
|
| 119 |
+
| [granite-8b-code-instruct-128k-Q3_K_S.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q3_K_S.gguf) | Q3_K_S | 3.304 GB | very small, high quality loss |
|
| 120 |
+
| [granite-8b-code-instruct-128k-Q3_K_M.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q3_K_M.gguf) | Q3_K_M | 3.674 GB | very small, high quality loss |
|
| 121 |
+
| [granite-8b-code-instruct-128k-Q3_K_L.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q3_K_L.gguf) | Q3_K_L | 3.993 GB | small, substantial quality loss |
|
| 122 |
+
| [granite-8b-code-instruct-128k-Q4_0.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q4_0.gguf) | Q4_0 | 4.276 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
|
| 123 |
+
| [granite-8b-code-instruct-128k-Q4_K_S.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q4_K_S.gguf) | Q4_K_S | 4.305 GB | small, greater quality loss |
|
| 124 |
+
| [granite-8b-code-instruct-128k-Q4_K_M.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q4_K_M.gguf) | Q4_K_M | 4.548 GB | medium, balanced quality - recommended |
|
| 125 |
+
| [granite-8b-code-instruct-128k-Q5_0.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q5_0.gguf) | Q5_0 | 5.190 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
|
| 126 |
+
| [granite-8b-code-instruct-128k-Q5_K_S.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q5_K_S.gguf) | Q5_K_S | 5.190 GB | large, low quality loss - recommended |
|
| 127 |
+
| [granite-8b-code-instruct-128k-Q5_K_M.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q5_K_M.gguf) | Q5_K_M | 5.330 GB | large, very low quality loss - recommended |
|
| 128 |
+
| [granite-8b-code-instruct-128k-Q6_K.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q6_K.gguf) | Q6_K | 6.161 GB | very large, extremely low quality loss |
|
| 129 |
+
| [granite-8b-code-instruct-128k-Q8_0.gguf](https://huggingface.co/tensorblock/granite-8b-code-instruct-128k-GGUF/blob/main/granite-8b-code-instruct-128k-Q8_0.gguf) | Q8_0 | 7.977 GB | very large, extremely low quality loss - not recommended |
|
| 130 |
|
| 131 |
|
| 132 |
## Downloading instruction
|