| |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| from PIL import Image |
| import torch |
|
|
| MODEL_ID = "unsloth/qwen2.5-vl-7b-instruct" |
|
|
| tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True) |
| model = AutoModelForCausalLM.from_pretrained( |
| MODEL_ID, torch_dtype=torch.float16, device_map="auto", trust_remote_code=True |
| ) |
|
|
| def infer(request): |
| messages = request.get("messages", []) |
| images = request.get("images", []) |
|
|
| inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device) |
| outputs = model.generate(**inputs, max_new_tokens=512) |
| return {"text": tokenizer.decode(outputs[0])} |
|
|
