| 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() |
