Spaces:
Running
on
Zero
Running
on
Zero
take off saving
Browse files- app_dialogue.py +0 -109
app_dialogue.py
CHANGED
@@ -361,79 +361,6 @@ FEATURES = datasets.Features(
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}
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def flag_dope(
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model_selector,
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chat_history,
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decoding_strategy,
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temperature,
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max_new_tokens,
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repetition_penalty,
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top_p,
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):
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images = []
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conversation = []
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for ex in chat_history:
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if isinstance(ex[0], dict):
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images.append(img_to_bytes(ex[0]["file"]["path"]))
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else:
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conversation.append({"User": ex[0], "Assistant": ex[1]})
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data = {
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"model_selector": [model_selector],
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"images": [images],
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"conversation": [conversation],
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"decoding_strategy": [decoding_strategy],
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"temperature": [temperature],
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"max_new_tokens": [max_new_tokens],
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"repetition_penalty": [repetition_penalty],
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"top_p": [top_p],
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}
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try:
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ds = datasets.load_dataset("HuggingFaceM4/dope-dataset-red-teaming", split="train", token=HF_WRITE_TOKEN)
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new_data = datasets.Dataset.from_dict(data, features=FEATURES)
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hf_dataset = datasets.concatenate_datasets([ds,new_data])
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except Exception:
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hf_dataset = datasets.Dataset.from_dict(data, features=FEATURES)
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hf_dataset.push_to_hub( "HuggingFaceM4/dope-dataset-red-teaming", split="train", token=HF_WRITE_TOKEN, private=True)
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def flag_problematic(
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model_selector,
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chat_history,
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decoding_strategy,
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temperature,
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max_new_tokens,
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repetition_penalty,
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top_p,
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):
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images = []
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conversation = []
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for ex in chat_history:
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if isinstance(ex[0], dict):
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images.append(img_to_bytes(ex[0]["file"]["path"]))
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else:
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conversation.append({"User": ex[0], "Assistant": ex[1]})
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data = {
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"model_selector": [model_selector],
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"images": [images],
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"conversation": [conversation],
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"decoding_strategy": [decoding_strategy],
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"temperature": [temperature],
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"max_new_tokens": [max_new_tokens],
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"repetition_penalty": [repetition_penalty],
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"top_p": [top_p],
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}
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try:
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ds = datasets.load_dataset("HuggingFaceM4/problematic-dataset-red-teaming", split="train", token=HF_WRITE_TOKEN)
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new_data = datasets.Dataset.from_dict(data, features=FEATURES)
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hf_dataset = datasets.concatenate_datasets([ds,new_data])
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except Exception:
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hf_dataset = datasets.Dataset.from_dict(data, features=FEATURES)
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hf_dataset.push_to_hub( "HuggingFaceM4/problematic-dataset-red-teaming", split="train", token=HF_WRITE_TOKEN, private=True)
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# Hyper-parameters for generation
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max_new_tokens = gr.Slider(
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@@ -491,8 +418,6 @@ chatbot = gr.Chatbot(
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height=450,
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)
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# Using Flagging for saving dope and problematic examples
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image_flag = gr.Image(visible=False)
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with gr.Blocks(
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fill_height=True,
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css=""".gradio-container .avatar-container {height: 40px width: 40px !important;} #duplicate-button {margin: auto; color: white; background: #f1a139; border-radius: 100vh;}""",
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@@ -550,39 +475,5 @@ with gr.Blocks(
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top_p,
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],
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with gr.Group():
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with gr.Row():
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with gr.Column(scale=1, min_width=50):
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dope_bttn = gr.Button("Dope🔥")
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with gr.Column(scale=1, min_width=50):
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problematic_bttn = gr.Button("Problematic😬")
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dope_bttn.click(
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fn=flag_dope,
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inputs=[
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model_selector,
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chatbot,
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decoding_strategy,
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temperature,
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max_new_tokens,
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repetition_penalty,
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top_p,
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],
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outputs=None,
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preprocess=False,
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)
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problematic_bttn.click(
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fn=flag_problematic,
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inputs=[
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model_selector,
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chatbot,
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decoding_strategy,
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temperature,
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max_new_tokens,
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repetition_penalty,
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top_p,
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],
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outputs=None,
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preprocess=False,
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)
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demo.launch()
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}
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)
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# Hyper-parameters for generation
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max_new_tokens = gr.Slider(
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height=450,
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)
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with gr.Blocks(
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fill_height=True,
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css=""".gradio-container .avatar-container {height: 40px width: 40px !important;} #duplicate-button {margin: auto; color: white; background: #f1a139; border-radius: 100vh;}""",
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top_p,
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],
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)
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demo.launch()
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