messages = [{"role": "user", "content": prompt}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
model_inputs = tokenizer([text], return_tensors="pt").to(device)
generated_ids = model.generate(model_inputs.input_ids, max_new_tokens=512, do_sample=True)
generated_ids = [output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]

Qwen2Config
[[autodoc]] Qwen2Config
Qwen2Tokenizer
[[autodoc]] Qwen2Tokenizer
    - save_vocabulary
Qwen2TokenizerFast
[[autodoc]] Qwen2TokenizerFast
Qwen2Model
[[autodoc]] Qwen2Model
    - forward
Qwen2ForCausalLM
[[autodoc]] Qwen2ForCausalLM
    - forward
Qwen2ForSequenceClassification
[[autodoc]] Qwen2ForSequenceClassification
    - forward