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Runtime error
DongfuJiang
commited on
Commit
•
bf0e8d1
1
Parent(s):
abbe14c
update
Browse files
app.py
CHANGED
@@ -20,11 +20,11 @@ DEFAULT_FUSER_MAX_NEW_TOKENS = 256
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# MIX-INSTRUCT
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EXAMPLES_DATASET = load_dataset("llm-blender/mix-instruct", split='validation')
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SHUFFLED_EXAMPLES_DATASET = EXAMPLES_DATASET.shuffle(seed=42)
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MIX_INSTRUCT_EXAMPLES = []
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CANDIDATE_MAP = {}
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for i, example in enumerate(SHUFFLED_EXAMPLES_DATASET):
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MIX_INSTRUCT_EXAMPLES.append([
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example['instruction'],
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example['input'],
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@@ -88,7 +88,7 @@ def get_mt_bench_human_judge_examples(model_a, model_b, conversation_a, conversa
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blender = llm_blender.Blender()
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blender.loadranker("llm-blender/PairRM")
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blender.loadfuser("llm-blender/gen_fuser_3b")
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def update_base_llms_num(k, llm_outputs):
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k = int(k)
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@@ -214,9 +214,9 @@ with gr.Blocks(theme='ParityError/Anime') as demo:
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outputs=[compare_result, compare_result_prob],
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)
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clear_button.click(
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fn=lambda: ["", ""],
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inputs=[],
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outputs=[compare_result, compare_result_prob],
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)
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hhh_dummy_textbox1 = gr.Textbox(lines=1, label="subset", placeholder="", show_label=False, visible=False)
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@@ -328,207 +328,207 @@ with gr.Blocks(theme='ParityError/Anime') as demo:
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)
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with gr.Tab("LLM-Blender"):
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# MIX-INSTRUCT
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EXAMPLES_DATASET = load_dataset("llm-blender/mix-instruct", split='validation', streaming=True)
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SHUFFLED_EXAMPLES_DATASET = EXAMPLES_DATASET.shuffle(seed=42)
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MIX_INSTRUCT_EXAMPLES = []
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CANDIDATE_MAP = {}
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for i, example in enumerate(SHUFFLED_EXAMPLES_DATASET.take(100)):
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MIX_INSTRUCT_EXAMPLES.append([
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example['instruction'],
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example['input'],
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blender = llm_blender.Blender()
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blender.loadranker("llm-blender/PairRM")
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# blender.loadfuser("llm-blender/gen_fuser_3b")
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def update_base_llms_num(k, llm_outputs):
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k = int(k)
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outputs=[compare_result, compare_result_prob],
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)
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clear_button.click(
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fn=lambda: ["", "", "", "", ""],
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inputs=[],
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outputs=[instruction, response1, response2, compare_result, compare_result_prob],
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)
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hhh_dummy_textbox1 = gr.Textbox(lines=1, label="subset", placeholder="", show_label=False, visible=False)
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)
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# with gr.Tab("LLM-Blender"):
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# # llm-blender interface
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# with gr.Row():
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# gr.Markdown(descriptions.LLM_BLENDER_OVERALL_DESC)
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# gr.Image("https://github.com/yuchenlin/LLM-Blender/blob/main/docs/llm_blender.png?raw=true", height=300)
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# gr.Markdown("## Input and Base LLMs")
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# with gr.Row():
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# with gr.Column():
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# inst_textbox = gr.Textbox(lines=1, label="Instruction", placeholder="Enter instruction here", show_label=True)
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# input_textbox = gr.Textbox(lines=4, label="Input Context", placeholder="Enter input context here", show_label=True)
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# with gr.Column():
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# saved_llm_outputs = gr.State(value={})
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# with gr.Group():
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# selected_base_llm_name_dropdown = gr.Dropdown(label="Base LLM",
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# choices=[f"LLM-{i+1}" for i in range(MIN_BASE_LLM_NUM)], value="LLM-1", show_label=True)
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# selected_base_llm_output = gr.Textbox(lines=4, label="LLM-1 (Click Save to save current content)",
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# placeholder="Enter LLM-1 output here", show_label=True)
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# with gr.Row():
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# base_llm_outputs_save_button = gr.Button('Save', variant='primary')
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# base_llm_outputs_clear_single_button = gr.Button('Clear Single', variant='primary')
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# base_llm_outputs_clear_all_button = gr.Button('Clear All', variant='primary')
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# base_llms_num = gr.Slider(
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# label='Number of base llms',
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# minimum=MIN_BASE_LLM_NUM,
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# maximum=MAX_BASE_LLM_NUM,
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# step=1,
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# value=MIN_BASE_LLM_NUM,
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# )
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# blender_state = gr.State(value={})
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# saved_rank_outputs = gr.State(value=[])
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# saved_fuse_outputs = gr.State(value=[])
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# gr.Markdown("## Blender Outputs")
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# with gr.Group():
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# rank_outputs = gr.Textbox(lines=1, label="Ranking outputs", placeholder="Ranking outputs", show_label=True)
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# fuser_outputs = gr.Textbox(lines=4, label="Fusing outputs", placeholder="Fusing outputs", show_label=True)
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# with gr.Row():
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# rank_button = gr.Button('Rank LLM Outputs', variant='primary')
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# fuse_button = gr.Button('Fuse Top-K ranked outputs', variant='primary')
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# clear_button = gr.Button('Clear Blender Outputs', variant='primary')
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# blender_config = gr.State(value={
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# "source_max_length": DEFAULT_SOURCE_MAX_LENGTH,
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# "candidate_max_length": DEFAULT_CANDIDATE_MAX_LENGTH,
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# "top_k_for_fuser": 3,
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# "max_new_tokens": DEFAULT_FUSER_MAX_NEW_TOKENS,
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# "temperature": 0.7,
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# "top_p": 1.0,
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# })
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# with gr.Accordion(label='Advanced options', open=False):
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# source_max_length = gr.Slider(
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# label='Max length of Instruction + Input',
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# minimum=1,
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# maximum=SOURCE_MAX_LENGTH,
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# step=1,
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# value=DEFAULT_SOURCE_MAX_LENGTH,
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# )
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# candidate_max_length = gr.Slider(
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# label='Max length of LLM-Output Candidate',
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# minimum=1,
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# maximum=CANDIDATE_MAX_LENGTH,
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# step=1,
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# value=DEFAULT_CANDIDATE_MAX_LENGTH,
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# )
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# top_k_for_fuser = gr.Slider(
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# label='Top-k ranked candidates to fuse',
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# minimum=1,
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# maximum=3,
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# step=1,
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# value=3,
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# )
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# max_new_tokens = gr.Slider(
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# label='Max new tokens fuser can generate',
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# minimum=1,
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# maximum=FUSER_MAX_NEW_TOKENS,
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# step=1,
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# value=DEFAULT_FUSER_MAX_NEW_TOKENS,
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# )
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# temperature = gr.Slider(
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# label='Temperature of fuser generation',
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# minimum=0.1,
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# maximum=2.0,
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# step=0.1,
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# value=0.7,
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# )
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# top_p = gr.Slider(
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# label='Top-p of fuser generation',
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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=1.0,
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# )
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# examples_dummy_textbox = gr.Textbox(lines=1, label="", placeholder="", show_label=False, visible=False)
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# batch_examples = gr.Examples(
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# examples=MIX_INSTRUCT_EXAMPLES,
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# fn=get_preprocess_examples,
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# cache_examples=True,
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# examples_per_page=5,
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# inputs=[inst_textbox, input_textbox],
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# outputs=[inst_textbox, input_textbox, base_llms_num, examples_dummy_textbox],
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# )
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# base_llms_num.input(
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# fn=update_base_llms_num,
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# inputs=[base_llms_num, saved_llm_outputs],
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# outputs=[selected_base_llm_name_dropdown, saved_llm_outputs],
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# )
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# examples_dummy_textbox.change(
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# fn=update_base_llm_dropdown_along_examples,
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# inputs=[inst_textbox, input_textbox],
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# outputs=[saved_llm_outputs, rank_outputs, fuser_outputs, selected_base_llm_name_dropdown],
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# ).then(
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# fn=display_llm_output,
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# inputs=[saved_llm_outputs, selected_base_llm_name_dropdown],
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# outputs=selected_base_llm_output,
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# )
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# selected_base_llm_name_dropdown.change(
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# fn=display_llm_output,
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# inputs=[saved_llm_outputs, selected_base_llm_name_dropdown],
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# outputs=selected_base_llm_output,
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# )
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# base_llm_outputs_save_button.click(
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# fn=save_llm_output,
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# inputs=[selected_base_llm_name_dropdown, selected_base_llm_output, saved_llm_outputs],
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# outputs=saved_llm_outputs,
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# )
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# base_llm_outputs_clear_all_button.click(
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# fn=lambda: [{}, ""],
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# inputs=[],
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# outputs=[saved_llm_outputs, selected_base_llm_output],
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# )
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# base_llm_outputs_clear_single_button.click(
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# fn=lambda: "",
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# inputs=[],
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# outputs=selected_base_llm_output,
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# )
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# rank_button.click(
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# fn=check_save_ranker_inputs,
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# inputs=[inst_textbox, input_textbox, saved_llm_outputs, blender_config],
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# outputs=blender_state,
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# ).success(
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# fn=llms_rank,
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# inputs=[inst_textbox, input_textbox, saved_llm_outputs, blender_config],
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# outputs=[saved_rank_outputs, rank_outputs],
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# )
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# fuse_button.click(
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# fn=check_fuser_inputs,
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# inputs=[blender_state, blender_config, saved_rank_outputs],
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# outputs=[],
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# ).success(
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# fn=llms_fuse,
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# inputs=[blender_state, blender_config, saved_rank_outputs],
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# outputs=[saved_fuse_outputs, fuser_outputs],
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# )
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# clear_button.click(
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# fn=lambda: ["", "", {}, []],
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# inputs=[],
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# outputs=[rank_outputs, fuser_outputs, blender_state, saved_rank_outputs],
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# )
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# # update blender config
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# source_max_length.change(
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# fn=lambda x, y: y.update({"source_max_length": x}) or y,
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# inputs=[source_max_length, blender_config],
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# outputs=blender_config,
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# )
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# candidate_max_length.change(
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# fn=lambda x, y: y.update({"candidate_max_length": x}) or y,
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# inputs=[candidate_max_length, blender_config],
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# outputs=blender_config,
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# )
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# top_k_for_fuser.change(
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# fn=lambda x, y: y.update({"top_k_for_fuser": x}) or y,
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# inputs=[top_k_for_fuser, blender_config],
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# outputs=blender_config,
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# )
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# max_new_tokens.change(
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# fn=lambda x, y: y.update({"max_new_tokens": x}) or y,
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# inputs=[max_new_tokens, blender_config],
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# outputs=blender_config,
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# )
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# temperature.change(
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# fn=lambda x, y: y.update({"temperature": x}) or y,
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# inputs=[temperature, blender_config],
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# outputs=blender_config,
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# )
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# top_p.change(
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# fn=lambda x, y: y.update({"top_p": x}) or y,
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# inputs=[top_p, blender_config],
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# outputs=blender_config,
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# )
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