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--- |
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pipeline_tag: text-generation |
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inference: false |
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license: apache-2.0 |
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datasets: |
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- codeparrot/github-code-clean |
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- bigcode/starcoderdata |
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- open-web-math/open-web-math |
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- math-ai/StackMathQA |
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metrics: |
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- code_eval |
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library_name: transformers |
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tags: |
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- code |
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- granite |
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- TensorBlock |
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- GGUF |
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base_model: ibm-granite/granite-3b-code-base-128k |
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model-index: |
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- name: granite-3b-code-base-128k |
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results: |
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- task: |
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type: text-generation |
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dataset: |
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name: HumanEvalSynthesis (Python) |
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type: bigcode/humanevalpack |
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metrics: |
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- type: pass@1 |
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value: 36.0 |
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name: pass@1 |
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verified: false |
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- type: pass@1 |
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value: 30.5 |
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name: pass@1 |
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verified: false |
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- type: pass@1 |
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value: 22.4 |
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name: pass@1 |
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verified: false |
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- type: pass@1 |
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value: 19.9 |
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name: pass@1 |
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verified: false |
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- task: |
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type: text-generation |
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dataset: |
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name: RepoQA (Python@16K) |
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type: repoqa |
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metrics: |
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- type: pass@1 (thresh=0.5) |
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value: 40.0 |
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name: pass@1 (thresh=0.5) |
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verified: false |
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- type: pass@1 (thresh=0.5) |
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value: 36.0 |
|
name: pass@1 (thresh=0.5) |
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verified: false |
|
- type: pass@1 (thresh=0.5) |
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value: 37.0 |
|
name: pass@1 (thresh=0.5) |
|
verified: false |
|
- type: pass@1 (thresh=0.5) |
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value: 27.0 |
|
name: pass@1 (thresh=0.5) |
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verified: false |
|
- type: pass@1 (thresh=0.5) |
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value: 29.0 |
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name: pass@1 (thresh=0.5) |
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verified: false |
|
- task: |
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type: text-generation |
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dataset: |
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name: LCC (Balanced) |
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type: lcc |
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metrics: |
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- type: Exact Match@4K |
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value: 54.6 |
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name: Exact Match@4K |
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verified: false |
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- type: Exact Match@8K |
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value: 56.8 |
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name: Exact Match@8K |
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verified: false |
|
- type: Exact Match@16K |
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value: 52.2 |
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name: Exact Match@16K |
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verified: false |
|
- type: Exact Match@32K |
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value: 57.8 |
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name: Exact Match@32K |
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verified: false |
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- task: |
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type: text-generation |
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dataset: |
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name: RepoBench-P (Balanced) |
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type: repobench |
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metrics: |
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- type: Exact Match@4K |
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value: 39.8 |
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name: Exact Match@4K |
|
verified: false |
|
- type: Exact Match@8K |
|
value: 46.8 |
|
name: Exact Match@8K |
|
verified: false |
|
- type: Exact Match@16K |
|
value: 43.1 |
|
name: Exact Match@16K |
|
verified: false |
|
- type: Exact Match@32K |
|
value: 45.3 |
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name: Exact Match@32K |
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verified: false |
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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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## ibm-granite/granite-3b-code-base-128k - GGUF |
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|
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This repo contains GGUF format model files for [ibm-granite/granite-3b-code-base-128k](https://huggingface.co./ibm-granite/granite-3b-code-base-128k). |
|
|
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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 b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d). |
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|
|
<div style="text-align: left; margin: 20px 0;"> |
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<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;"> |
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Run them on the TensorBlock client using your local machine ↗ |
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</a> |
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</div> |
|
|
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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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| -------- | ---------- | --------- | ----------- | |
|
| [granite-3b-code-base-128k-Q2_K.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q2_K.gguf) | Q2_K | 1.339 GB | smallest, significant quality loss - not recommended for most purposes | |
|
| [granite-3b-code-base-128k-Q3_K_S.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q3_K_S.gguf) | Q3_K_S | 1.552 GB | very small, high quality loss | |
|
| [granite-3b-code-base-128k-Q3_K_M.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q3_K_M.gguf) | Q3_K_M | 1.727 GB | very small, high quality loss | |
|
| [granite-3b-code-base-128k-Q3_K_L.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q3_K_L.gguf) | Q3_K_L | 1.876 GB | small, substantial quality loss | |
|
| [granite-3b-code-base-128k-Q4_0.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q4_0.gguf) | Q4_0 | 1.997 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
|
| [granite-3b-code-base-128k-Q4_K_S.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q4_K_S.gguf) | Q4_K_S | 2.014 GB | small, greater quality loss | |
|
| [granite-3b-code-base-128k-Q4_K_M.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q4_K_M.gguf) | Q4_K_M | 2.132 GB | medium, balanced quality - recommended | |
|
| [granite-3b-code-base-128k-Q5_0.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q5_0.gguf) | Q5_0 | 2.417 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
|
| [granite-3b-code-base-128k-Q5_K_S.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q5_K_S.gguf) | Q5_K_S | 2.417 GB | large, low quality loss - recommended | |
|
| [granite-3b-code-base-128k-Q5_K_M.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q5_K_M.gguf) | Q5_K_M | 2.486 GB | large, very low quality loss - recommended | |
|
| [granite-3b-code-base-128k-Q6_K.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q6_K.gguf) | Q6_K | 2.862 GB | very large, extremely low quality loss | |
|
| [granite-3b-code-base-128k-Q8_0.gguf](https://huggingface.co./tensorblock/granite-3b-code-base-128k-GGUF/blob/main/granite-3b-code-base-128k-Q8_0.gguf) | Q8_0 | 3.706 GB | very large, extremely low quality loss - not recommended | |
|
|
|
|
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## Downloading instruction |
|
|
|
### Command line |
|
|
|
Firstly, install Huggingface Client |
|
|
|
```shell |
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pip install -U "huggingface_hub[cli]" |
|
``` |
|
|
|
Then, downoad the individual model file the a local directory |
|
|
|
```shell |
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huggingface-cli download tensorblock/granite-3b-code-base-128k-GGUF --include "granite-3b-code-base-128k-Q2_K.gguf" --local-dir MY_LOCAL_DIR |
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``` |
|
|
|
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: |
|
|
|
```shell |
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huggingface-cli download tensorblock/granite-3b-code-base-128k-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
|
``` |
|
|
