from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
tokenizer = AutoTokenizer.from_pretrained("Minami-su/Qwen1.5-14B-Chat_mistral")
model = AutoModelForCausalLM.from_pretrained("Minami-su/Qwen1.5-14B-Chat_mistral", torch_dtype="auto", device_map="auto")
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)

messages = [
    {"role": "user", "content": "Who are you?"}
]
inputs = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
inputs = inputs.to("cuda")
generate_ids = model.generate(inputs,max_length=32768, streamer=streamer)

Test

load in 4bit

hf-causal (pretrained=Qwen1.5-14B-Chat), limit: None, provide_description: False, num_fewshot: 0, batch_size: 16
|    Task     |Version| Metric |Value |   |Stderr|
|-------------|------:|--------|-----:|---|-----:|
|arc_challenge|      0|acc     |0.4437|±  |0.0145|
|             |       |acc_norm|0.4718|±  |0.0146|
|truthfulqa_mc|      1|mc1     |0.4468|±  |0.0174|
|             |       |mc2     |0.6310|±  |0.0157|
|winogrande   |      0|acc     |0.6788|±  |0.0131|

load in 4bit

hf-causal (pretrained=Qwen1.5-14B-Chat_mistral), limit: None, provide_description: False, num_fewshot: 0, batch_size: 16
|    Task     |Version| Metric |Value |   |Stderr|
|-------------|------:|--------|-----:|---|-----:|
|arc_challenge|      0|acc     |0.4445|±  |0.0145|
|             |       |acc_norm|0.4718|±  |0.0146|
|truthfulqa_mc|      1|mc1     |0.4468|±  |0.0174|
|             |       |mc2     |0.6310|±  |0.0157|
|winogrande   |      0|acc     |0.6788|±  |0.0131|