| import pickle, torch, gradio as gr |
| from model.fih import Fih |
|
|
| with open("tokenizer.pkl", 'rb') as f: |
| tokenizer = pickle.load(f) |
|
|
| model = Fih() |
|
|
| def respond(message, history): |
| tokens = tokenizer.encode(message, return_tensor="pt") |
| generated = tokens.tolist() |
| for _ in range(60): |
| logits = model.forward_pass(torch.tensor(generated)) |
| probs = torch.softmax(logits[-1] / 1.2, dim=-1) |
| next_token = torch.multinomial(probs, 1).item() |
| generated.append(next_token) |
|
|
| if next_token == 0: |
| break |
|
|
| return tokenizer.decode(generated) |
|
|
| app = gr.ChatInterface(fn=respond, title="FIH1 | Chat 🐟") |
|
|
| |
|
|
| app.launch() |
