Update app.py
Browse files
app.py
CHANGED
@@ -9,26 +9,24 @@ DiarizationLM GGUF inference on CPU
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"""
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model_path = "models"
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model_name = "model-unsloth.BF16.gguf"
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hf_hub_download(repo_id="google/DiarizationLM-13b-Fisher-v1", filename=model_name, local_dir=model_path, local_dir_use_symlinks=False)
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print("Start the model init process")
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model = GPT4All(model_name, model_path, allow_download = False, device="cpu")
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print("Finish the model init process")
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model.config["promptTemplate"] = "{0} --> "
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model.config["systemPrompt"] = ""
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model._is_chat_session_activated = False
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max_new_tokens = 2048
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print("Finish the model config process")
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def generater(message, history, temperature, top_p, top_k):
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prompt = model.config["promptTemplate"].format(message)
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outputs = []
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for token in model.generate(prompt=prompt, temp=
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outputs.append(token)
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yield "".join(outputs)
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@@ -43,44 +41,12 @@ print("Create chatbot")
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chatbot = gr.Chatbot()
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print("Created chatbot")
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print("Add additional_inputs")
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additional_inputs=[
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gr.Slider(
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label="temperature",
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value=0.0,
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minimum=0.0,
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maximum=2.0,
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step=0.05,
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interactive=True,
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info="Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.",
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),
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gr.Slider(
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label="top_p",
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value=1.0,
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minimum=0.0,
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maximum=1.0,
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step=0.01,
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interactive=True,
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info="0.1 means only the tokens comprising the top 10% probability mass are considered. Suggest set to 1 and use temperature. 1 means 100% and will disable it",
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),
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gr.Slider(
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label="top_k",
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value=50,
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minimum=0,
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maximum=1000,
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step=1,
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interactive=True,
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info="limits candidate tokens to a fixed number after sorting by probability. Setting it higher than the vocabulary size deactivates this limit.",
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)
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]
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print("Added additional_inputs")
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iface = gr.ChatInterface(
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fn = generater,
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title=title,
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description = description,
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chatbot=chatbot,
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additional_inputs=
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examples=[
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["<speaker:1> Hello, how are you doing <speaker:2> today? I am doing well."],
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]
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"""
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model_path = "models"
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model_name = "q4_k_m.gguf"
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hf_hub_download(repo_id="google/DiarizationLM-13b-Fisher-v1", filename=model_name, local_dir=model_path, local_dir_use_symlinks=False)
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print("Start the model init process")
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model = GPT4All(model_name=model_name, model_path=model_path, allow_download = False, device="cpu")
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print("Finish the model init process")
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model.config["promptTemplate"] = "{0} --> "
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model.config["systemPrompt"] = ""
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model._is_chat_session_activated = False
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print("Finish the model config process")
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def generater(message, history, temperature, top_p, top_k):
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prompt = model.config["promptTemplate"].format(message)
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max_new_tokens = round(len(prompt) / 3.0 * 1.2)
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outputs = []
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for token in model.generate(prompt=prompt, temp=0.0, top_k = 50, top_p = 0.9, max_tokens = max_new_tokens, streaming=True):
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outputs.append(token)
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yield "".join(outputs)
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chatbot = gr.Chatbot()
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print("Created chatbot")
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iface = gr.ChatInterface(
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fn = generater,
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title=title,
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description = description,
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chatbot=chatbot,
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additional_inputs=[],
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examples=[
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["<speaker:1> Hello, how are you doing <speaker:2> today? I am doing well."],
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]
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