Spaces:
Sleeping
Sleeping
import gradio as gr | |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
import torch | |
import spaces | |
model_name = "Sakalti/SakalFusion-7B-Alpha" | |
model = AutoModelForCausalLM.from_pretrained( | |
model_name, | |
torch_dtype=torch.bfloat16, | |
device_map="auto" | |
) | |
tokenizer = AutoTokenizer.from_pretrained(model_name) | |
def generate(prompt, history, top_p, top_k, max_new_tokens, repetition_penalty, temperature): | |
messages = [ | |
{"role": "system", "content": "γγͺγγ―γγ¬γ³γγͺγΌγͺγγ£γγγγγγ§γγ"}, | |
{"role": "user", "content": prompt} | |
] | |
text = tokenizer.apply_chat_template( | |
messages, | |
tokenize=False, | |
add_generation_prompt=True | |
) | |
model_inputs = tokenizer([text], return_tensors="pt").to(model.device) | |
generated_ids = model.generate( | |
**model_inputs, | |
max_new_tokens=max_new_tokens, | |
top_p=top_p, | |
top_k=top_k, | |
repetition_penalty=repetition_penalty, | |
temperature=temperature | |
) | |
generated_ids = [ | |
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) | |
] | |
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] | |
return response, history + [[prompt, response]] | |
with gr.Blocks() as demo: | |
chatbot = gr.Chatbot() | |
msg = gr.Textbox() | |
clear = gr.Button("Clear") | |
with gr.Row(): | |
top_p = gr.Slider(0.0, 1.0, value=0.9, label="Top P") | |
top_k = gr.Slider(0, 100, value=50, label="Top K") | |
max_new_tokens = gr.Slider(1, 2048, value=864, label="Max New Tokens") | |
repetition_penalty = gr.Slider(1.0, 2.0, value=1.2, label="Repetition Penalty") | |
temperature = gr.Slider(0.1, 1.0, value=0.7, label="Temperature") | |
def respond(message, chat_history, top_p, top_k, max_new_tokens, repetition_penalty, temperature): | |
bot_message, chat_history = generate(message, chat_history, top_p, top_k, max_new_tokens, repetition_penalty, temperature) | |
return "", chat_history, chat_history | |
msg.submit(respond, [msg, chatbot, top_p, top_k, max_new_tokens, repetition_penalty, temperature], [msg, chatbot, chatbot]) | |
clear.click(lambda: ([], []), None, [chatbot, msg]) | |
demo.launch(share=True) |