Update README.md

README.md

@@ -1,22 +1,15 @@
 ---
 tags:
-- autotrain
 - text-generation-inference
 - text-generation
 - peft
 library_name: transformers
 base_model: meta-llama/Meta-Llama-3-8B
 widget:
-  - messages:
-      - role: user
-        content: What is your favorite condiment?
+  - input: Le médecin a prescrit de l'amoxicilline pour traiter l'infection pulmonaire chronique du patient diabétique.
 license: other
 ---
 
-# Model Trained Using AutoTrain
-
-This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
-
 # Usage
 
 ```python
@@ -33,14 +26,11 @@ model = AutoModelForCausalLM.from_pretrained(
 ).eval()
 
 # Prompt content: "hi"
-messages = [
-    {"role": "user", "content": "hi"}
-]
+input = "Le médecin a prescrit de l'amoxicilline pour traiter l'infection pulmonaire chronique du patient diabétique."
 
-input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
+input_ids = tokenizer(input, tokenize=True, return_tensors='pt')
 output_ids = model.generate(input_ids.to('cuda'))
 response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
 
-# Model response: "Hello! How can I assist you today?"
 print(response)
 ```