Update README.md

README.md

@@ -23,6 +23,34 @@ French-Alpaca is a general model and can itself be finetuned to be specialized f
 
 The fine-tuning method is inspired from https://crfm.stanford.edu/2023/03/13/alpaca.html
 
+### Usage & Test
+
+```python
+#!pip install transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "jpacifico/French-Alpaca-7B-Instruct-beta"
+messages = [{"role": "user", "content": "Rédige un article sur la fin des vendanges dans le Mâconnais."}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+outputs = pipeline(prompt, max_new_tokens=128, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```
+
+You can test French-Alpaca with this dedicated and compatible colab notebook (with GPU) :  
+https://github.com/jpacifico/French-Alpaca/blob/main/French_Alpaca_inference_test_colab.ipynb  
+
 ### Limitations
 
 The French-Alpaca model is a quick demonstration that a base 7B model can be easily fine-tuned to specialize in a particular language.