Vigogne-instruct-bloom-7b1 is a
bigscience/bloom-7b1 model fine-tuned to follow the 🇫🇷 French instructions.
For more information, please visit the Github repo:
https://github.com/bofenghuang/vigogneUsage and License Notices: Same as
Stanford Alpaca, Vigogne is intended and licensed for research use only. The dataset is CC BY NC 4.0 (allowing only non-commercial use) and models trained using the dataset should not be used outside of research purposes.
This repo only contains the low-rank adapter. In order to access the complete model, you also need to load the base LLM model and tokenizer.
1from peft import PeftModel
2from transformers import AutoModelForCausalLM, AutoTokenizer
3
4base_model_name_or_path = "bigscience/bloom-7b1"
5lora_model_name_or_path = "bofenghuang/vigogne-instruct-bloom-7b1"
6
7tokenizer = AutoTokenizer.from_pretrained(base_model_name_or_path, padding_side="right", use_fast=False)
8model = AutoModelForCausalLM.from_pretrained(
9 base_model_name_or_path,
10 load_in_8bit=True,
11 torch_dtype=torch.float16,
12 device_map="auto",
13)
14model = PeftModel.from_pretrained(model, lora_model_name_or_path)
You can infer this model by using the following Google Colab Notebook.
Vigogne is still under development, and there are many limitations that have to be addressed. Please note that it is possible that the model generates harmful or biased content, incorrect information or generally unhelpful answers.
