153 lines
6.6 KiB
Markdown
153 lines
6.6 KiB
Markdown
---
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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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- bigcode/commitpackft
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- TIGER-Lab/MathInstruct
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- meta-math/MetaMathQA
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- glaiveai/glaive-code-assistant-v3
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- glaive-function-calling-v2
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- bugdaryan/sql-create-context-instruction
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- garage-bAInd/Open-Platypus
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- nvidia/HelpSteer
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- bigcode/self-oss-instruct-sc2-exec-filter-50k
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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-8b-code-instruct-128k
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model-index:
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- name: granite-8B-Code-instruct-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: 62.2
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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: 51.4
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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: 38.9
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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: 38.3
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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: 73.0
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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: 37.0
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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: 73.0
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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: 62.0
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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: 63.0
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name: pass@1 (thresh=0.5)
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verified: false
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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-8b-code-instruct-128k - GGUF
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This repo contains GGUF format model files for [ibm-granite/granite-8b-code-instruct-128k](https://huggingface.co/ibm-granite/granite-8b-code-instruct-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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System:
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{system_prompt}
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Question:
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{prompt}
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Answer:
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```
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## Model file specification
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [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 |
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| [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 |
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| [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 |
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| [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 |
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| [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 |
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| [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 |
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| [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 |
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| [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 |
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| [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 |
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| [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 |
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| [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 |
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| [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 |
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## Downloading instruction
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### Command line
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Firstly, install Huggingface Client
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```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-8b-code-instruct-128k-GGUF --include "granite-8b-code-instruct-128k-Q2_K.gguf" --local-dir MY_LOCAL_DIR
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```
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If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
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```shell
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huggingface-cli download tensorblock/granite-8b-code-instruct-128k-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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```
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