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Update app
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app.py
CHANGED
@@ -2,9 +2,9 @@ import gradio as gr
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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# Define the function to handle text generation
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def generate_text(model_name, text, num_beams, max_length, top_p, temperature, repetition_penalty, no_repeat_ngram_size):
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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# Initialize pipeline with explicit model and tokenizer
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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@@ -32,7 +32,8 @@ inputs_component = [
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gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Top p"),
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gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Temperature"),
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gr.Slider(minimum=1.0, maximum=5.0, step=0.5, label="Repetition Penalty"),
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gr.Slider(minimum=2, maximum=5, step=1, label="No Repeat Ngram Size")
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]
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# Setup the interface with live=False to require button press
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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# Define the function to handle text generation
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def generate_text(model_name, text, num_beams, max_length, top_p, temperature, repetition_penalty, no_repeat_ngram_size, token):
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tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=token)
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model = AutoModelForCausalLM.from_pretrained(model_name, use_auth_token=token)
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# Initialize pipeline with explicit model and tokenizer
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Top p"),
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gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Temperature"),
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gr.Slider(minimum=1.0, maximum=5.0, step=0.5, label="Repetition Penalty"),
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gr.Slider(minimum=2, maximum=5, step=1, label="No Repeat Ngram Size"),
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gr.Textbox(placeholder="Enter your Hugging Face token here...", label="Hugging Face Token", type="password")
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]
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# Setup the interface with live=False to require button press
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