| import gradio as gr | |
| import torch | |
| import transformers | |
| from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed | |
| set_seed(42) | |
| tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-3B-v1") | |
| model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-3B-v1", torch_dtype=torch.bfloat16) | |
| def Bemenet(bemenet): | |
| prompt = "<human>: Who is Alan Turing?\n<bot>:" | |
| inputs = tokenizer(prompt, return_tensors='pt').to(model.device) | |
| input_length = inputs.input_ids.shape[1] | |
| outputs = model.generate( | |
| **inputs, max_new_tokens=128, do_sample=True, temperature=0.7, top_p=0.7, top_k=50, return_dict_in_generate=True | |
| ) | |
| token = outputs.sequences[0, input_length:] | |
| output_str = tokenizer.decode(token) | |
| return output_str | |
| interface = gr.Interface(fn=Bemenet, | |
| title="Cím..", | |
| description="Leírás..", | |
| inputs="text", | |
| outputs="text") | |
| interface.launch() |