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---
pipeline_tag: text-generation
inference: true
widget:
- text: 'def print_hello_world():'
example_title: Hello world
group: Python
license: bigscience-openrail-m
pretrain-datasets:
- books
- arxiv
- c4
- falcon-refinedweb
- wiki
- github-issues
- stack_markdown
- self-made dataset of permissive github code
datasets:
- bigcode/the-stack-dedup
- rombodawg/2XUNCENSORED_MegaCodeTraining188k
- bigcode/commitpackft
metrics:
- code_eval
library_name: transformers
tags:
- code
- TensorBlock
- GGUF
language:
- en
base_model: smallcloudai/Refact-1_6B-fim
model-index:
- name: Refact-1.6B
results:
- task:
type: text-generation
dataset:
name: HumanEval
type: openai_humaneval
metrics:
- type: pass@1
value: 32.0
name: pass@1 (T=0.01)
verified: false
- type: pass@1
value: 31.5
name: pass@1 (T=0.2)
verified: false
- type: pass@10
value: 53.0
name: pass@10 (T=0.8)
verified: false
- type: pass@100
value: 76.9
name: pass@100 (T=0.8)
verified: false
- task:
type: text-generation
dataset:
name: HumanEvalSynthesize Python
type: bigcode/humanevalpack
metrics:
- type: pass@1
value: 35.8
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 31.6
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 29.1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: -1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 26.3
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: -1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: -1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 18.38
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 12.28
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 15.12
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: -1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 13.17
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 2.8
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: -1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 26.92
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 26.85
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 30.76
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: -1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 25.94
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 8.44
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: -1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 26.46
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 17.86
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 20.94
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: -1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 18.78
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: -1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: -1
name: pass@1 (T=0.2)
verified: false
- task:
type: text-generation
dataset:
name: MBPP
type: mbpp
metrics:
- type: pass@1
value: 31.15
name: pass@1 (T=0.01)
verified: false
- task:
type: text-generation
dataset:
name: DS-1000 (Overall Completion)
type: ds1000
metrics:
- type: pass@1
value: 10.1
name: pass@1 (T=0.2)
verified: false
- task:
type: text-generation
dataset:
name: MultiPL-HumanEval (C++)
type: nuprl/MultiPL-E
metrics:
- type: pass@1
value: 21.61
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 13.91
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 9.5
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 53.57
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 21.58
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 13.75
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 26.88
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 15.26
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 23.04
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 12.1
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 29.6
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 13.77
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 12.68
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 4.29
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 19.54
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 18.33
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 5.7
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 17.68
name: pass@1 (T=0.2)
verified: false
- type: pass@1
value: 25
name: pass@1 (T=0.2)
verified: false
---
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<div style="display: flex; flex-direction: column; align-items: flex-start;">
<p style="margin-top: 0.5em; margin-bottom: 0em;">
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>
</p>
</div>
</div>
## smallcloudai/Refact-1_6B-fim - GGUF
This repo contains GGUF format model files for [smallcloudai/Refact-1_6B-fim](https://huggingface.co/smallcloudai/Refact-1_6B-fim).
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).
<div style="text-align: left; margin: 20px 0;">
<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;">
Run them on the TensorBlock client using your local machine ↗
</a>
</div>
## Prompt template
```
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Refact-1_6B-fim-Q2_K.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q2_K.gguf) | Q2_K | 0.581 GB | smallest, significant quality loss - not recommended for most purposes |
| [Refact-1_6B-fim-Q3_K_S.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q3_K_S.gguf) | Q3_K_S | 0.673 GB | very small, high quality loss |
| [Refact-1_6B-fim-Q3_K_M.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q3_K_M.gguf) | Q3_K_M | 0.739 GB | very small, high quality loss |
| [Refact-1_6B-fim-Q3_K_L.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q3_K_L.gguf) | Q3_K_L | 0.795 GB | small, substantial quality loss |
| [Refact-1_6B-fim-Q4_0.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q4_0.gguf) | Q4_0 | 0.857 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Refact-1_6B-fim-Q4_K_S.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q4_K_S.gguf) | Q4_K_S | 0.862 GB | small, greater quality loss |
| [Refact-1_6B-fim-Q4_K_M.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q4_K_M.gguf) | Q4_K_M | 0.902 GB | medium, balanced quality - recommended |
| [Refact-1_6B-fim-Q5_0.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q5_0.gguf) | Q5_0 | 1.030 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Refact-1_6B-fim-Q5_K_S.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q5_K_S.gguf) | Q5_K_S | 1.030 GB | large, low quality loss - recommended |
| [Refact-1_6B-fim-Q5_K_M.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q5_K_M.gguf) | Q5_K_M | 1.053 GB | large, very low quality loss - recommended |
| [Refact-1_6B-fim-Q6_K.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q6_K.gguf) | Q6_K | 1.214 GB | very large, extremely low quality loss |
| [Refact-1_6B-fim-Q8_0.gguf](https://huggingface.co/tensorblock/Refact-1_6B-fim-GGUF/blob/main/Refact-1_6B-fim-Q8_0.gguf) | Q8_0 | 1.571 GB | very large, extremely low quality loss - not recommended |
## Downloading instruction
### Command line
Firstly, install Huggingface Client
```shell
pip install -U "huggingface_hub[cli]"
```
Then, downoad the individual model file the a local directory
```shell
huggingface-cli download tensorblock/Refact-1_6B-fim-GGUF --include "Refact-1_6B-fim-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
```shell
huggingface-cli download tensorblock/Refact-1_6B-fim-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
|