File size: 6,440 Bytes

---
license: bigscience-bloom-rail-1.0
language:
- ak
- ar
- as
- bm
- bn
- ca
- code
- en
- es
- eu
- fon
- fr
- gu
- hi
- id
- ig
- ki
- kn
- lg
- ln
- ml
- mr
- ne
- nso
- ny
- or
- pa
- pt
- rn
- rw
- sn
- st
- sw
- ta
- te
- tn
- ts
- tum
- tw
- ur
- vi
- wo
- xh
- yo
- zh
- zhs
- zht
- zu
pipeline_tag: text-generation
tags:
- TensorBlock
- GGUF
base_model: bigscience/bloom-7b1
---

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## bigscience/bloom-7b1 - GGUF

This repo contains GGUF format model files for [bigscience/bloom-7b1](https://huggingface.co/bigscience/bloom-7b1).

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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## Prompt template


```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [bloom-7b1-Q2_K.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q2_K.gguf) | Q2_K | 3.201 GB | smallest, significant quality loss - not recommended for most purposes |
| [bloom-7b1-Q3_K_S.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q3_K_S.gguf) | Q3_K_S | 3.631 GB | very small, high quality loss |
| [bloom-7b1-Q3_K_M.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q3_K_M.gguf) | Q3_K_M | 4.137 GB | very small, high quality loss |
| [bloom-7b1-Q3_K_L.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q3_K_L.gguf) | Q3_K_L | 4.422 GB | small, substantial quality loss |
| [bloom-7b1-Q4_0.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q4_0.gguf) | Q4_0 | 4.505 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [bloom-7b1-Q4_K_S.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q4_K_S.gguf) | Q4_K_S | 4.529 GB | small, greater quality loss |
| [bloom-7b1-Q4_K_M.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q4_K_M.gguf) | Q4_K_M | 4.907 GB | medium, balanced quality - recommended |
| [bloom-7b1-Q5_0.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q5_0.gguf) | Q5_0 | 5.328 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [bloom-7b1-Q5_K_S.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q5_K_S.gguf) | Q5_K_S | 5.328 GB | large, low quality loss - recommended |
| [bloom-7b1-Q5_K_M.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q5_K_M.gguf) | Q5_K_M | 5.631 GB | large, very low quality loss - recommended |
| [bloom-7b1-Q6_K.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q6_K.gguf) | Q6_K | 6.202 GB | very large, extremely low quality loss |
| [bloom-7b1-Q8_0.gguf](https://huggingface.co/tensorblock/bloom-7b1-GGUF/blob/main/bloom-7b1-Q8_0.gguf) | Q8_0 | 8.028 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/bloom-7b1-GGUF --include "bloom-7b1-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/bloom-7b1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```