Update README.md

README.md

@@ -44,10 +44,28 @@ tokenizer = transformers.AutoTokenizer.from_pretrained(model_id)
 messages=[
     { 'role': 'user', 'content': "write a quick sort algorithm in python."}
 ]
-inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
+messages = [
+    {"role": "system", "content": "You are world class python programmer with deep expertise in Ploty for data visualisation and analysis. Given a input question and schema, answer with correct python plotly code"},
+    {"role": "user", "content": prompt},
+]
+
+input_ids = tokenizer1.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+
+terminators = [
+    tokenizer1.eos_token_id,
+    tokenizer1.convert_tokens_to_ids("<|eot_id|>")
+]
+
+input_tokens = tokenizer1.convert_ids_to_tokens(tokenizer1.encode(input_ids))
+
+results = model1.generate_batch([input_tokens], include_prompt_in_result=False, max_length=700, sampling_temperature=0.6, sampling_topp=0.9, end_token=terminators)
+output = tokenizer1.decode(results[0].sequences_ids[0])
 
-outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, top_k=50, top_p=0.95, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id)
-print(tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True))
+print(output)
 ```
 
 ### 4. License