Vigogne Instruct 13B - A French instruction-following LLaMa model HF
These files are fp16 HF format model files for Vigogne Instruct 13B - A French instruction-following LLaMa model.
These files are the result of merging the LoRA and then uploading in fp16.
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- 4-bit GPTQ models for GPU inference
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- Unquantised fp16 model in HF format
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Original model card: Vigogne Instruct 13B - A French instruction-following LLaMa model
Vigogne-instruct-13b: A French Instruction-following LLaMA Model
Vigogne-instruct-13b is a LLaMA-13B model fine-tuned to follow the 🇫🇷 French instructions.
For more information, please visit the Github repo: https://github.com/bofenghuang/vigogne
Usage 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.
Usage
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.
from peft import PeftModel
from transformers import LlamaForCausalLM, LlamaTokenizer
base_model_name_or_path = "name/or/path/to/hf/llama/13b/model"
lora_model_name_or_path = "bofenghuang/vigogne-instruct-13b"
tokenizer = LlamaTokenizer.from_pretrained(base_model_name_or_path, padding_side="right", use_fast=False)
model = LlamaForCausalLM.from_pretrained(
base_model_name_or_path,
load_in_8bit=True,
torch_dtype=torch.float16,
device_map="auto",
)
model = PeftModel.from_pretrained(model, lora_model_name_or_path)
You can infer this model by using the following Google Colab Notebook.
Limitations
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.
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