up

README.md

@@ -19,7 +19,7 @@ inference: false
 
 # Vigogne-LoRA-7b: A French Instruct LLaMA Model
 
-Vigogne-LoRA-7b is a [LLaMA-7B](https://huggingface.co/decapoda-research/llama-7b-hf) model fine-tuned on the translated [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca) dataset to follow the French 🇫🇷 instructions.
+Vigogne-LoRA-7b is a [LLaMA-7B](https://huggingface.co/decapoda-research/llama-7b-hf) model fine-tuned on the translated [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca) dataset to follow the 🇫🇷 French instructions.
 
 For more information, please visit the Github repo: https://github.com/bofenghuang/vigogne
 
@@ -27,7 +27,7 @@ For more information, please visit the Github repo: https://github.com/bofenghua
 
 ## Usage
 
-This repo contains only its low-rank adapter. In order to use it, you also need to load the base LLM model and tokenizer.
+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.
 
 ```python
 from peft import PeftModel
@@ -42,7 +42,7 @@ model = LlamaForCausalLM.from_pretrained(
 model = PeftModel.from_pretrained(model, "bofenghuang/vigogne-lora-7b")
 ```
 
-You can infer with this model using the following Google Colab Notebook.
+You can infer this model by using the following Google Colab Notebook.
 
 <a href="https://colab.research.google.com/github/bofenghuang/vigogne/blob/main/infer.ipynb" target="_blank"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>