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Runtime error
Runtime error
Josh Nguyen
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•
d81d6d2
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Parent(s):
6e7d907
First commit
Browse files- app.py +124 -0
- requirements.txt +8 -0
app.py
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from threading import Thread
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import gradio as gr
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import torch
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from transformers import (
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AutoModelForCausalLM,
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AutoTokenizer,
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AutoConfig,
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TextIteratorStreamer
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)
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MODEL_ID = "universeTBD/astrollama"
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WINDOW_SIZE = 4096
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DEVICE = "cuda"
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config = AutoConfig.from_pretrained(pretrained_model_name_or_path=MODEL_ID)
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tokenizer = AutoTokenizer.from_pretrained(
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pretrained_model_name_or_path=MODEL_ID
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)
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model = AutoModelForCausalLM.from_pretrained(
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pretrained_model_name_or_path=MODEL_ID,
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config=config,
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device_map="auto",
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use_safetensors=True,
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trust_remote_code=True,
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load_in_4bit=True,
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torch_dtype=torch.bfloat16
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)
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def generate_text(prompt: str,
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max_new_tokens: int = 512,
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temperature: float = 0.5,
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top_p: float = 0.95,
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top_k: int = 50) -> str:
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# Encode the prompt
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inputs = tokenizer([prompt],
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return_tensors="pt",
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add_special_tokens=False,
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return_token_type_ids=False)
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inputs = inputs.to(DEVICE)
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# Prepare arguments for generation
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input_length = inputs["input_ids"].shape[-1]
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max_new_tokens = min(max_new_tokens, WINDOW_SIZE - input_length)
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if temperature >= 1.0:
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temperature = 0.99
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elif temperature <= 0.0:
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temperature = 0.01
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if top_p > 1.0 or top_p <= 0.0:
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top_p = 1.0
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if top_k <= 0:
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top_k = 100
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streamer = TextIteratorStreamer(tokenizer,
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timeout=10.,
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skip_prompt=True,
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skip_special_tokens=True)
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generation_kwargs = dict(
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inputs=inputs,
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streamer=inputs,
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max_new_tokens=max_new_tokens,
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do_sample=True,
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return_full_text=True,
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top_p=top_p,
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top_k=top_k,
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temperature=temperature,
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num_beams=1,
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)
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# Generate text
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thread = Thread(target=model.generate, kwargs=generation_kwargs)
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thread.start()
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# outputs = []
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for text in streamer:
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return text
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demo = gr.Interface(
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fn=generate_text,
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inputs=[
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# Prompt
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gr.Textbox(
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label="Prompt",
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container=False,
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show_label=False,
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placeholder="Enter some text...",
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scale=10,
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),
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gr.Slider(
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label="Temperature",
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minimum=0.01,
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maximum=0.99,
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step=0.01,
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value=0.5,
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),
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gr.Slider(
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label="Top-p (for sampling)",
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minimum=0.05,
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maximum=1.0,
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step=0.05,
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value=0.95,
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),
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gr.Slider(
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label='Top-k (for sampling)',
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minimum=1,
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maximum=1000,
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step=1,
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value=100,
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)
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],
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outputs=[
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gr.Textbox(
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container=False,
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show_label=False,
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placeholder="Generated output...",
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scale=10,
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)
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],
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)
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demo.queue(max_size=20).launch(server_port=7878)
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requirements.txt
ADDED
@@ -0,0 +1,8 @@
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accelerate==0.21.0
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bitsandbytes==0.40.2
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gradio==3.37.0
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protobuf==3.20.3
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scipy==1.11.1
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sentencepiece==0.1.99
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torch==2.0.1
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transformers==4.31.0
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