Text Generation
Transformers
Safetensors
PyTorch
mistral
finetuned
quantized
4-bit precision
gptq
Safetensors
text-generation-inference
Merge
7b
mistralai/Mistral-7B-Instruct-v0.2
HuggingFaceH4/zephyr-7b-beta
Generated from Trainer
en
dataset:HuggingFaceH4/ultrachat_200k
dataset:HuggingFaceH4/ultrafeedback_binarized
arxiv:2305.18290
arxiv:2310.16944
Eval Results
Inference Endpoints
conversational
license: apache-2.0 | |
tags: | |
- finetuned | |
- quantized | |
- 4-bit | |
- gptq | |
- transformers | |
- safetensors | |
- mistral | |
- text-generation | |
- Safetensors | |
- text-generation-inference | |
- merge | |
- 7b | |
- mistralai/Mistral-7B-Instruct-v0.2 | |
- HuggingFaceH4/zephyr-7b-beta | |
- pytorch | |
- generated_from_trainer | |
- en | |
- dataset:HuggingFaceH4/ultrachat_200k | |
- dataset:HuggingFaceH4/ultrafeedback_binarized | |
- arxiv:2305.18290 | |
- arxiv:2310.16944 | |
- base_model:mistralai/Mistral-7B-v0.1 | |
- license:mit | |
- model-index | |
- autotrain_compatible | |
- endpoints_compatible | |
- region:us | |
- license:apache-2.0 | |
model_name: zephyr-7b-beta-Mistral-7B-Instruct-v0.2-GPTQ | |
base_model: MaziyarPanahi/zephyr-7b-beta-Mistral-7B-Instruct-v0.2 | |
inference: false | |
model_creator: MaziyarPanahi | |
pipeline_tag: text-generation | |
quantized_by: MaziyarPanahi | |
# Description | |
[MaziyarPanahi/zephyr-7b-beta-Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/MaziyarPanahi/zephyr-7b-beta-Mistral-7B-Instruct-v0.2-GPTQ) is a quantized (GPTQ) version of [MaziyarPanahi/zephyr-7b-beta-Mistral-7B-Instruct-v0.2](https://huggingface.co/MaziyarPanahi/zephyr-7b-beta-Mistral-7B-Instruct-v0.2) | |
## How to use | |
### Install the necessary packages | |
``` | |
pip install --upgrade accelerate auto-gptq transformers | |
``` | |
### Example Python code | |
```python | |
from transformers import AutoTokenizer, pipeline | |
from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig | |
import torch | |
model_id = "MaziyarPanahi/zephyr-7b-beta-Mistral-7B-Instruct-v0.2-GPTQ" | |
quantize_config = BaseQuantizeConfig( | |
bits=4, | |
group_size=128, | |
desc_act=False | |
) | |
model = AutoGPTQForCausalLM.from_quantized( | |
model_id, | |
use_safetensors=True, | |
device="cuda:0", | |
quantize_config=quantize_config) | |
tokenizer = AutoTokenizer.from_pretrained(model_id) | |
pipe = pipeline( | |
"text-generation", | |
model=model, | |
tokenizer=tokenizer, | |
max_new_tokens=512, | |
temperature=0.7, | |
top_p=0.95, | |
repetition_penalty=1.1 | |
) | |
outputs = pipe("What is a large language model?") | |
print(outputs[0]["generated_text"]) | |
``` |