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Runtime error
| import torch | |
| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig | |
| model_id = "ALLaM-AI/ALLaM-7B-Instruct-preview" | |
| bnb_config = BitsAndBytesConfig( | |
| load_in_4bit=True, | |
| bnb_4bit_compute_dtype=torch.float16, | |
| bnb_4bit_quant_type="nf4", | |
| bnb_4bit_use_double_quant=True | |
| ) | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| tokenizer.pad_token = tokenizer.eos_token | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_id, | |
| quantization_config=bnb_config, | |
| device_map="auto" | |
| ) | |
| def generate_answer(question): | |
| prompt = f"أجب بالعربية الفصحى فقط:\n{question}\n" | |
| inputs = tokenizer(prompt, return_tensors="pt").to("cuda") | |
| output = model.generate( | |
| **inputs, | |
| max_new_tokens=200, | |
| temperature=0.7, | |
| do_sample=True, | |
| pad_token_id=tokenizer.eos_token_id | |
| ) | |
| return tokenizer.decode(output[0], skip_special_tokens=True) | |
| demo = gr.Interface( | |
| fn=generate_answer, | |
| inputs="text", | |
| outputs="text", | |
| ) | |
| demo.launch() |