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1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model_name = "your-username/your-model-name"
4tokenizer = AutoTokenizer.from_pretrained(model_name)
5model = AutoModelForCausalLM.from_pretrained(model_name)
6
7# Chat with the model
8messages = [
9 {"role": "system", "content": "You are a helpful assistant."},
10 {"role": "user", "content": "Hello, how are you?"}
11]
12
13# Apply chat template
14chat_text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
15inputs = tokenizer(chat_text, return_tensors="pt")
16
17# Generate response
18outputs = model.generate(**inputs, max_new_tokens=100)
19response = tokenizer.decode(outputs[0], skip_special_tokens=True)
20print(response)1from transformers import pipeline
2
3chat = pipeline("text-generation", model="your-username/your-model-name")
4
5messages = [
6 {"role": "user", "content": "What is the capital of France?"}
7]
8
9response = chat(messages, max_new_tokens=100)
10print(response)1@misc{yourmodel2024,
2 title={Chat Model},
3 author={Your Name},
4 year={2024},
5 howpublished={\url{https://huggingface.co/your-username/your-model-name}}
6}