Delete app.py

app.py

@@ -1,106 +0,0 @@
-import gradio as gr
-import torch
-from transformers import (
-    AutoModelForCausalLM,
-    AutoTokenizer,
-    TextIteratorStreamer,
-)
-import os
-from threading import Thread
-import spaces
-import time
-import subprocess
-
-subprocess.run(
-    "pip install flash-attn --no-build-isolation",
-    env={"FLASH_ATTENTION_SKIP_CUDA_BUILD": "TRUE"},
-    shell=True,
-)
-
-token = os.environ["HF_TOKEN"]
-
-
-model = AutoModelForCausalLM.from_pretrained(
-    "rdrede/mbn",
-    token=token,
-    trust_remote_code=True,
-    torch_dtype=torch.bfloat16
-)
-tok = AutoTokenizer.from_pretrained("rdrede/mbn", token=token)
-terminators = [
-    tok.eos_token_id,
-]
-
-if torch.cuda.is_available():
-    device = torch.device("cuda")
-    print(f"Using GPU: {torch.cuda.get_device_name(device)}")
-else:
-    device = torch.device("cpu")
-    print("Using CPU")
-
-model = model.to(device)
-# Dispatch Errors
-
-
-@spaces.GPU(duration=60)
-def chat(message, history, temperature, do_sample, max_tokens):
-    chat = []
-    for item in history:
-        chat.append({"role": "user", "content": item[0]})
-        if item[1] is not None:
-            chat.append({"role": "assistant", "content": item[1]})
-    chat.append({"role": "user", "content": message})
-    messages = tok.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
-    model_inputs = tok([messages], return_tensors="pt").to(device)
-    streamer = TextIteratorStreamer(
-        tok, timeout=20.0, skip_prompt=True, skip_special_tokens=True
-    )
-    generate_kwargs = dict(
-        model_inputs,
-        streamer=streamer,
-        max_new_tokens=max_tokens,
-        do_sample=True,
-        temperature=temperature,
-        eos_token_id=terminators,
-    )
-
-    if temperature == 0:
-        generate_kwargs["do_sample"] = False
-
-    t = Thread(target=model.generate, kwargs=generate_kwargs)
-    t.start()
-
-    partial_text = ""
-    for new_text in streamer:
-        partial_text += new_text
-        yield partial_text
-
-    yield partial_text
-
-
-demo = gr.ChatInterface(
-    fn=chat,
-    examples=[["Write me a poem about Machine Learning."]],
-    # multimodal=False,
-    additional_inputs_accordion=gr.Accordion(
-        label="⚙️ Parameters", open=False, render=False
-    ),
-    additional_inputs=[
-        gr.Slider(
-            minimum=0, maximum=1, step=0.1, value=0.9, label="Temperature", render=False
-        ),
-        gr.Checkbox(label="Sampling", value=True),
-        gr.Slider(
-            minimum=128,
-            maximum=4096,
-            step=1,
-            value=512,
-            label="Max new tokens",
-            render=False,
-        ),
-    ],
-    stop_btn="Stop Generation",
-    title="Chat With LLMs",
-    description="Now Running [microsoft/phi-4](https://huggingface.co/microsoft/phi-4)",
-)
-demo.launch()