Create app.py

app.py

@@ -0,0 +1,104 @@
+from huggingface_hub import InferenceClient
+import gradio as gr
+import os
+
+API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.1"
+HF_TOKEN = os.environ['HF_TOKEN']
+
+client = InferenceClient(
+    API_URL,
+    headers = {"Authorization" : f"Bearer {HF_TOKEN}"},
+)
+
+client_unverified = InferenceClient(
+    "mistralai/Mistral-7B-Instruct-v0.1"
+)
+
+def format_prompt(message, history):
+  prompt = "<s>"
+  for user_prompt, bot_response in history:
+    prompt += f"[INST] {user_prompt} [/INST]"
+    prompt += f" {bot_response}</s> "
+  prompt += f"[INST] {message} [/INST]"
+  return prompt
+
+def generate(prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,):
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+    generate_kwargs = dict(
+        temperature=temperature,
+        max_new_tokens=max_new_tokens,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        seed=42,
+    )
+
+    formatted_prompt = format_prompt(prompt, history)
+    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    output = ""
+    for response in stream:
+        output += response.token.text
+        yield output
+    return output
+
+additional_inputs=[
+    gr.Slider(
+        label="Temperature",
+        value=0.9,
+        minimum=0.0,
+        maximum=1.0,
+        step=0.05,
+        interactive=True,
+        info="Higher values produce more diverse outputs",
+    ),
+    gr.Slider(
+        label="Max new tokens",
+        value=256,
+        minimum=0,
+        maximum=1048,
+        step=64,
+        interactive=True,
+        info="The maximum numbers of new tokens",
+    ),
+    gr.Slider(
+        label="Top-p (nucleus sampling)",
+        value=0.90,
+        minimum=0.0,
+        maximum=1,
+        step=0.05,
+        interactive=True,
+        info="Higher values sample more low-probability tokens",
+    ),
+    gr.Slider(
+        label="Repetition penalty",
+        value=1.2,
+        minimum=1.0,
+        maximum=2.0,
+        step=0.05,
+        interactive=True,
+        info="Penalize repeated tokens",
+    )
+]
+
+css = """
+  #mkd {
+    height: 500px;
+    overflow: auto;
+    border: 1px solid #ccc;
+  }
+"""
+
+with gr.Blocks(css=css, theme="NoCrypt/miku@1.2.1") as demo:
+    gr.HTML("<h1><center>MistralTalk<h1><center>")
+    gr.HTML("<h3><center>💬<h3><center>")
+    gr.HTML("<h3><center>Learn more about the model <a href='https://huggingface.co/docs/transformers/main/model_doc/mistral'>here</a>. 📚<h3><center>")
+    gr.ChatInterface(
+        generate,
+        additional_inputs=additional_inputs,
+        examples=[["What is the secret to life?"], ["How the universe works?"],["What can you do?"]]
+    )
+
+demo.queue(max_size=100).launch(debug=True)