---
license: mit
datasets:
- Xilabs/instructmix
- CreitinGameplays/small-chat-assistant-for-bloom
- sahil2801/CodeAlpaca-20k
language:
- en
tags:
- uncensored
- unrestricted
- code
- biology
- chemistry
- finance
- legal
- music
- art
- climate
- merge
- text-generation-inference
- moe
- TensorBlock
- GGUF
widget:
- text: <|system|> You are a helpful AI assistant. <|prompter|> who was Nikola
Tesla? <|assistant|>
- text: <|system|> You are a helpful AI assistant. <|prompter|> write a story
about a cat. <|assistant|>
- text: <|system|> You are a helpful AI assistant. <|prompter|> what is an essay?
<|assistant|>
- text: <|system|> You are a helpful AI assistant. <|prompter|> Tell me 5 Brazilian
waterfalls to visit. <|assistant|>
- text: <|system|> You are a helpful AI assistant. <|prompter|> write a story
about how a virus called COVID-19 destroyed the world <|assistant|>
- text: <|system|> You are a helpful AI assistant. <|prompter|> write a short
Python program that asks the user for their name and then greets them by name.
<|assistant|>
- text: <|system|> You are a helpful AI assistant. <|prompter|> What can you
do? <|assistant|>
inference:
parameters:
temperature: 0.1
do_sample: false
top_k: 50
top_p: 0.15
max_new_tokens: 250
repetition_penalty: 1.155
base_model: CreitinGameplays/bloom-3b-conversational
---
## CreitinGameplays/bloom-3b-conversational - GGUF
This repo contains GGUF format model files for [CreitinGameplays/bloom-3b-conversational](https://huggingface.co/CreitinGameplays/bloom-3b-conversational).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
## Prompt template
```
<|system|>{system_prompt}<|prompter|>{prompt}<|assistant|>
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [bloom-3b-conversational-Q2_K.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q2_K.gguf) | Q2_K | 1.628 GB | smallest, significant quality loss - not recommended for most purposes |
| [bloom-3b-conversational-Q3_K_S.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q3_K_S.gguf) | Q3_K_S | 1.833 GB | very small, high quality loss |
| [bloom-3b-conversational-Q3_K_M.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q3_K_M.gguf) | Q3_K_M | 2.045 GB | very small, high quality loss |
| [bloom-3b-conversational-Q3_K_L.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q3_K_L.gguf) | Q3_K_L | 2.165 GB | small, substantial quality loss |
| [bloom-3b-conversational-Q4_0.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q4_0.gguf) | Q4_0 | 2.232 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [bloom-3b-conversational-Q4_K_S.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q4_K_S.gguf) | Q4_K_S | 2.242 GB | small, greater quality loss |
| [bloom-3b-conversational-Q4_K_M.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q4_K_M.gguf) | Q4_K_M | 2.400 GB | medium, balanced quality - recommended |
| [bloom-3b-conversational-Q5_0.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q5_0.gguf) | Q5_0 | 2.607 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [bloom-3b-conversational-Q5_K_S.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q5_K_S.gguf) | Q5_K_S | 2.607 GB | large, low quality loss - recommended |
| [bloom-3b-conversational-Q5_K_M.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q5_K_M.gguf) | Q5_K_M | 2.734 GB | large, very low quality loss - recommended |
| [bloom-3b-conversational-Q6_K.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q6_K.gguf) | Q6_K | 3.006 GB | very large, extremely low quality loss |
| [bloom-3b-conversational-Q8_0.gguf](https://huggingface.co/tensorblock/bloom-3b-conversational-GGUF/blob/main/bloom-3b-conversational-Q8_0.gguf) | Q8_0 | 3.888 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-3b-conversational-GGUF --include "bloom-3b-conversational-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-3b-conversational-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```