| import gradio as gr |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| import torch |
|
|
| |
| model_name = "mistralai/Mistral-7B-Instruct" # Poți schimba cu un alt model |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
| model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto") |
|
|
| def chat(user_input): |
| inputs = tokenizer(user_input, return_tensors="pt").to("cuda") |
| output = model.generate(**inputs, max_length=300) |
| response = tokenizer.decode(output[0], skip_special_tokens=True) |
| return response |
|
|
| |
| iface = gr.Interface( |
| fn=chat, |
| inputs=gr.Textbox(lines=5, placeholder="Scrie aici..."), |
| outputs="text", |
| title="NanAI Scribo", |
| description="Chatbot AI specializat în metafizică, filozofie și terapii holistice." |
| ) |
|
|
| iface.launch() |
|
|