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README (1).md

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+---
+title: Llama3-8B-SFT-code Bagel-bnb-4bit
+emoji: 🥸
+colorFrom: green
+colorTo: blue
+sdk: gradio
+sdk_version: 4.31.5
+app_file: app.py
+pinned: false
+license: llama3
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import spaces
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import os
+import gradio as gr
+import sentencepiece
+
+
+os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:120'
+model_id = "thesven/Llama3-8B-SFT-code_bagel-bnb-4bit"
+tokenizer_path = "./"
+
+DESCRIPTION = """
+# thesven/Llama3-8B-SFT-code_bagel-bnb-4bit
+"""
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, device_map="auto", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="cuda", torch_dtype=torch.bfloat16, trust_remote_code=True)
+
+def format_prompt(user_message, system_message="You are an expert developer in all programming languages.  Help me with my code. Answer any questions I have with code examples."):
+    prompt = f"<|im_start|>assistant\n{system_message}<|im_end|>\n<|im_start|>\nuser\n{user_message}<|im_end|>\nassistant\n"
+    return prompt
+
+@spaces.GPU
+def predict(message, system_message, max_new_tokens=600, temperature=3.5, top_p=0.9, top_k=40, do_sample=False):
+    formatted_prompt = format_prompt(message, system_message)
+
+    input_ids = tokenizer.encode(formatted_prompt, return_tensors='pt')
+    input_ids = input_ids.to(model.device)
+
+    response_ids = model.generate(
+        input_ids,
+        max_length=max_new_tokens + input_ids.shape[1],
+        temperature=temperature,  
+        top_p=top_p,              
+        top_k=top_k,              
+        no_repeat_ngram_size=9,
+        pad_token_id=tokenizer.eos_token_id,
+        do_sample=do_sample
+    )
+
+    response = tokenizer.decode(response_ids[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
+    truncate_str = "<|im_end|>"
+    if truncate_str and truncate_str in response:
+        response = response.split(truncate_str)[0]
+
+    return [("bot", response)]    
+    
+with gr.Blocks() as demo:
+    gr.Markdown(DESCRIPTION)
+    with gr.Group():
+        system_prompt = gr.Textbox(placeholder='Provide a System Prompt In The First Person', label='System Prompt', lines=2, value="You are an expert developer in all programming languages.  Help me with my code. Answer any questions I have with code examples.")
+
+    with gr.Group():
+        chatbot = gr.Chatbot(label='thesven/Llama3-8B-SFT-code_bagel-bnb-4bit')
+
+    with gr.Group():
+        textbox = gr.Textbox(placeholder='Your Message Here', label='Your Message', lines=2)
+        submit_button = gr.Button('Submit', variant='primary')
+
+    with gr.Accordion(label='Advanced options', open=False):
+        max_new_tokens = gr.Slider(label='Max New Tokens', minimum=1, maximum=55000, step=1, value=512)
+        temperature = gr.Slider(label='Temperature', minimum=0.1, maximum=4.0, step=0.1, value=0.1)
+        top_p = gr.Slider(label='Top-P (nucleus sampling)', minimum=0.05, maximum=1.0, step=0.05, value=0.9)
+        top_k = gr.Slider(label='Top-K', minimum=1, maximum=1000, step=1, value=40)
+        do_sample_checkbox = gr.Checkbox(label='Disable for faster inference', value=True)
+
+    submit_button.click(
+        fn=predict,
+        inputs=[textbox, system_prompt, max_new_tokens, temperature, top_p, top_k, do_sample_checkbox],
+        outputs=chatbot
+    )
+
+demo.launch()

requirements.txt

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+accelerate
+bitsandbytes
+transformers
+spaces
+sentencepiece