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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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library_name: transformers |
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tags: |
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- language |
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- granite-3.0 |
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- TensorBlock |
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- GGUF |
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base_model: ibm-granite/granite-3.0-8b-instruct |
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model-index: |
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- name: granite-3.0-2b-instruct |
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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: IFEval |
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type: instruction-following |
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metrics: |
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- type: pass@1 |
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value: 52.27 |
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name: pass@1 |
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- type: pass@1 |
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value: 8.22 |
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name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: AGI-Eval |
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type: human-exams |
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metrics: |
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- type: pass@1 |
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value: 40.52 |
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name: pass@1 |
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- type: pass@1 |
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value: 65.82 |
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name: pass@1 |
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- type: pass@1 |
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value: 34.45 |
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name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: OBQA |
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type: commonsense |
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metrics: |
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- type: pass@1 |
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value: 46.6 |
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name: pass@1 |
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- type: pass@1 |
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value: 71.21 |
|
name: pass@1 |
|
- type: pass@1 |
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value: 82.61 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 77.51 |
|
name: pass@1 |
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- type: pass@1 |
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value: 60.32 |
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name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: BoolQ |
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type: reading-comprehension |
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metrics: |
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- type: pass@1 |
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value: 88.65 |
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name: pass@1 |
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- type: pass@1 |
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value: 21.58 |
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name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: ARC-C |
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type: reasoning |
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metrics: |
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- type: pass@1 |
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value: 64.16 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 33.81 |
|
name: pass@1 |
|
- type: pass@1 |
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value: 51.55 |
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name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: HumanEvalSynthesis |
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type: code |
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metrics: |
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- type: pass@1 |
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value: 64.63 |
|
name: pass@1 |
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- type: pass@1 |
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value: 57.16 |
|
name: pass@1 |
|
- type: pass@1 |
|
value: 65.85 |
|
name: pass@1 |
|
- type: pass@1 |
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value: 49.6 |
|
name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: GSM8K |
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type: math |
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metrics: |
|
- type: pass@1 |
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value: 68.99 |
|
name: pass@1 |
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- type: pass@1 |
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value: 30.94 |
|
name: pass@1 |
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- task: |
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type: text-generation |
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dataset: |
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name: PAWS-X (7 langs) |
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type: multilingual |
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metrics: |
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- type: pass@1 |
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value: 64.94 |
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name: pass@1 |
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- type: pass@1 |
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value: 48.2 |
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name: pass@1 |
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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-3.0-8b-instruct - GGUF |
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|
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This repo contains GGUF format model files for [ibm-granite/granite-3.0-8b-instruct](https://huggingface.co/ibm-granite/granite-3.0-8b-instruct). |
|
|
|
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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<|start_of_role|>system<|end_of_role|>{system_prompt}<|end_of_text|> |
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<|start_of_role|>user<|end_of_role|>{prompt}<|end_of_text|> |
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<|start_of_role|>assistant<|end_of_role|> |
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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 | |
|
| -------- | ---------- | --------- | ----------- | |
|
| [granite-3.0-8b-instruct-Q2_K.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q2_K.gguf) | Q2_K | 2.890 GB | smallest, significant quality loss - not recommended for most purposes | |
|
| [granite-3.0-8b-instruct-Q3_K_S.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q3_K_S.gguf) | Q3_K_S | 3.346 GB | very small, high quality loss | |
|
| [granite-3.0-8b-instruct-Q3_K_M.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q3_K_M.gguf) | Q3_K_M | 3.722 GB | very small, high quality loss | |
|
| [granite-3.0-8b-instruct-Q3_K_L.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q3_K_L.gguf) | Q3_K_L | 4.051 GB | small, substantial quality loss | |
|
| [granite-3.0-8b-instruct-Q4_0.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q4_0.gguf) | Q4_0 | 4.331 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
|
| [granite-3.0-8b-instruct-Q4_K_S.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q4_K_S.gguf) | Q4_K_S | 4.364 GB | small, greater quality loss | |
|
| [granite-3.0-8b-instruct-Q4_K_M.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q4_K_M.gguf) | Q4_K_M | 4.603 GB | medium, balanced quality - recommended | |
|
| [granite-3.0-8b-instruct-Q5_0.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q5_0.gguf) | Q5_0 | 5.259 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
|
| [granite-3.0-8b-instruct-Q5_K_S.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q5_K_S.gguf) | Q5_K_S | 5.259 GB | large, low quality loss - recommended | |
|
| [granite-3.0-8b-instruct-Q5_K_M.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q5_K_M.gguf) | Q5_K_M | 5.399 GB | large, very low quality loss - recommended | |
|
| [granite-3.0-8b-instruct-Q6_K.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q6_K.gguf) | Q6_K | 6.245 GB | very large, extremely low quality loss | |
|
| [granite-3.0-8b-instruct-Q8_0.gguf](https://huggingface.co/tensorblock/granite-3.0-8b-instruct-GGUF/blob/main/granite-3.0-8b-instruct-Q8_0.gguf) | Q8_0 | 8.088 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]" |
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``` |
|
|
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Then, downoad the individual model file the a local directory |
|
|
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```shell |
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huggingface-cli download tensorblock/granite-3.0-8b-instruct-GGUF --include "granite-3.0-8b-instruct-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 |
|
huggingface-cli download tensorblock/granite-3.0-8b-instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
|
``` |
|
|
