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Update app.py
Browse files
app.py
CHANGED
@@ -63,7 +63,7 @@ def evaluate(instruction, input, model, tokenizer):
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result.append( output.split("### Response:")[1].strip())
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return ' '.join(el for el in result)
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def inference(model_name, text, input):
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model = load_model(model_name)
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tokenizer = load_tokenizer(model_name)
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output = evaluate(instruction = text, input = input, model = model, tokenizer = tokenizer)
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@@ -72,43 +72,7 @@ def inference(model_name, text, input):
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def choose_model(name):
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return load_model(name), load_tokenizer(name)
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with
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temperature = gr.Slider(
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label="Temperature",
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value=0.7,
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minimum=0.0,
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maximum=1.0,
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step=0.1,
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interactive=True,
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info="Higher values produce more diverse outputs",
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)
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top_p = gr.Slider(
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label="Top-p (nucleus sampling)",
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value=0.9,
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minimum=0.0,
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maximum=1,
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step=0.05,
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interactive=True,
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info="Higher values sample more low-probability tokens",
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)
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max_new_tokens = gr.Slider(
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label="Max new tokens",
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value=1024,
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minimum=0,
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maximum=2048,
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step=4,
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interactive=True,
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info="The maximum numbers of new tokens",
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)
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repetition_penalty = gr.Slider(
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label="Repetition Penalty",
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value=1.2,
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minimum=0.0,
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maximum=10,
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step=0.1,
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interactive=True,
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info="The parameter for repetition penalty. 1.0 means no penalty.",
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)
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io = gr.Interface(
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inference,
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@@ -128,7 +92,7 @@ io = gr.Interface(
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#"stablelm-base-alpha-3b-Lora-polish",
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#"dolly-v2-3b-Lora-polish",
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#"LaMini-GPT-1.5B-Lora-polish"],
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]
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gr.Textbox(
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lines = 3,
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max_lines = 10,
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@@ -142,6 +106,42 @@ io = gr.Interface(
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placeholder = "Add context here",
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interactive = True,
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show_label = False
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)],
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outputs = [gr.Textbox(lines = 1, label = 'Pythia410m', interactive = False)],
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cache_examples = False,
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result.append( output.split("### Response:")[1].strip())
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return ' '.join(el for el in result)
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def inference(model_name, text, input, temperature, top_p, num_beams):
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model = load_model(model_name)
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tokenizer = load_tokenizer(model_name)
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output = evaluate(instruction = text, input = input, model = model, tokenizer = tokenizer)
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def choose_model(name):
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return load_model(name), load_tokenizer(name)
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with
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io = gr.Interface(
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inference,
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#"stablelm-base-alpha-3b-Lora-polish",
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#"dolly-v2-3b-Lora-polish",
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#"LaMini-GPT-1.5B-Lora-polish"],
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],
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gr.Textbox(
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lines = 3,
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max_lines = 10,
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placeholder = "Add context here",
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interactive = True,
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show_label = False
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),
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gr.Slider(
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label="Temperature",
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value=0.7,
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minimum=0.0,
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maximum=1.0,
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step=0.1,
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interactive=True,
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info="Higher values produce more diverse outputs",
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),
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gr.Slider(
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label="Top-p (nucleus sampling)",
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value=0.9,
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minimum=0.0,
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maximum=1,
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step=0.05,
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interactive=True,
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info="Higher values sample more low-probability tokens",
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),
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gr.Slider(
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label="Max new tokens",
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value=1024,
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minimum=0,
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maximum=2048,
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step=4,
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interactive=True,
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info="The maximum numbers of new tokens",
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),
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gr.Slider(
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label="Number of beams",
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value=2,
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minimum=0.0,
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maximum=5.0,
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step=1.0,
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interactive=True,
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info="The parameter for repetition penalty. 1.0 means no penalty.",
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)],
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outputs = [gr.Textbox(lines = 1, label = 'Pythia410m', interactive = False)],
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cache_examples = False,
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