Remove LoRA tab, move it into the Parameters menu

This commit is contained in:
oobabooga 2023-03-17 11:39:48 -03:00
parent 214dc6868e
commit 29fe7b1c74
3 changed files with 14 additions and 16 deletions

View File

@ -10,6 +10,8 @@ def add_lora_to_model(lora_name):
# Is there a more efficient way of returning to the base model? # Is there a more efficient way of returning to the base model?
if lora_name == "None": if lora_name == "None":
print(f"Reloading the model to remove the LoRA...")
shared.model, shared.tokenizer = load_model(shared.model_name) shared.model, shared.tokenizer = load_model(shared.model_name)
else: else:
print(f"Adding the LoRA {lora_name} to the model...")
shared.model = PeftModel.from_pretrained(shared.model, Path(f"loras/{lora_name}")) shared.model = PeftModel.from_pretrained(shared.model, Path(f"loras/{lora_name}"))

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@ -56,7 +56,7 @@ settings = {
}, },
'lora_prompts': { 'lora_prompts': {
'default': 'Common sense questions and answers\n\nQuestion: \nFactual answer:', 'default': 'Common sense questions and answers\n\nQuestion: \nFactual answer:',
'alpaca-lora-7b': "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n### Instruction:\nWrite a Python script that generates text using the transformers library.\n### Response:\n" 'alpaca-lora-7b': "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n### Instruction:\nWrite a poem about the transformers Python library. \nMention the word \"large language models\" in that poem.\n### Response:\n"
} }
} }

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@ -64,11 +64,15 @@ def load_model_wrapper(selected_model):
return selected_model return selected_model
def load_lora_wrapper(selected_lora): def load_lora_wrapper(selected_lora):
shared.lora_name = selected_lora
default_text = shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_name.lower())), 'default')]
if not shared.args.cpu: if not shared.args.cpu:
gc.collect() gc.collect()
torch.cuda.empty_cache() torch.cuda.empty_cache()
add_lora_to_model(selected_lora) add_lora_to_model(selected_lora)
return selected_lora
return selected_lora, default_text
def load_preset_values(preset_menu, return_dict=False): def load_preset_values(preset_menu, return_dict=False):
generate_params = { generate_params = {
@ -156,6 +160,10 @@ def create_settings_menus(default_preset):
shared.gradio['length_penalty'] = gr.Slider(-5, 5, value=generate_params['length_penalty'], label='length_penalty') shared.gradio['length_penalty'] = gr.Slider(-5, 5, value=generate_params['length_penalty'], label='length_penalty')
shared.gradio['early_stopping'] = gr.Checkbox(value=generate_params['early_stopping'], label='early_stopping') shared.gradio['early_stopping'] = gr.Checkbox(value=generate_params['early_stopping'], label='early_stopping')
with gr.Row():
shared.gradio['lora_menu'] = gr.Dropdown(choices=available_loras, value=shared.lora_name, label='LoRA')
ui.create_refresh_button(shared.gradio['lora_menu'], lambda : None, lambda : {'choices': get_available_loras()}, 'refresh-button')
with gr.Accordion('Soft prompt', open=False): with gr.Accordion('Soft prompt', open=False):
with gr.Row(): with gr.Row():
shared.gradio['softprompts_menu'] = gr.Dropdown(choices=available_softprompts, value='None', label='Soft prompt') shared.gradio['softprompts_menu'] = gr.Dropdown(choices=available_softprompts, value='None', label='Soft prompt')
@ -167,6 +175,7 @@ def create_settings_menus(default_preset):
shared.gradio['model_menu'].change(load_model_wrapper, [shared.gradio['model_menu']], [shared.gradio['model_menu']], show_progress=True) shared.gradio['model_menu'].change(load_model_wrapper, [shared.gradio['model_menu']], [shared.gradio['model_menu']], show_progress=True)
shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio['preset_menu']], [shared.gradio['do_sample'], shared.gradio['temperature'], shared.gradio['top_p'], shared.gradio['typical_p'], shared.gradio['repetition_penalty'], shared.gradio['encoder_repetition_penalty'], shared.gradio['top_k'], shared.gradio['min_length'], shared.gradio['no_repeat_ngram_size'], shared.gradio['num_beams'], shared.gradio['penalty_alpha'], shared.gradio['length_penalty'], shared.gradio['early_stopping']]) shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio['preset_menu']], [shared.gradio['do_sample'], shared.gradio['temperature'], shared.gradio['top_p'], shared.gradio['typical_p'], shared.gradio['repetition_penalty'], shared.gradio['encoder_repetition_penalty'], shared.gradio['top_k'], shared.gradio['min_length'], shared.gradio['no_repeat_ngram_size'], shared.gradio['num_beams'], shared.gradio['penalty_alpha'], shared.gradio['length_penalty'], shared.gradio['early_stopping']])
shared.gradio['lora_menu'].change(load_lora_wrapper, [shared.gradio['lora_menu']], [shared.gradio['lora_menu'], shared.gradio['textbox']], show_progress=True)
shared.gradio['softprompts_menu'].change(load_soft_prompt, [shared.gradio['softprompts_menu']], [shared.gradio['softprompts_menu']], show_progress=True) shared.gradio['softprompts_menu'].change(load_soft_prompt, [shared.gradio['softprompts_menu']], [shared.gradio['softprompts_menu']], show_progress=True)
shared.gradio['upload_softprompt'].upload(upload_soft_prompt, [shared.gradio['upload_softprompt']], [shared.gradio['softprompts_menu']]) shared.gradio['upload_softprompt'].upload(upload_soft_prompt, [shared.gradio['upload_softprompt']], [shared.gradio['softprompts_menu']])
@ -226,8 +235,8 @@ else:
shared.model_name = available_models[i] shared.model_name = available_models[i]
shared.model, shared.tokenizer = load_model(shared.model_name) shared.model, shared.tokenizer = load_model(shared.model_name)
if shared.args.lora: if shared.args.lora:
print(shared.args.lora)
shared.lora_name = shared.args.lora shared.lora_name = shared.args.lora
print(f"Adding the LoRA {shared.lora_name} to the model...")
add_lora_to_model(shared.lora_name) add_lora_to_model(shared.lora_name)
# Default UI settings # Default UI settings
@ -419,19 +428,6 @@ def create_interface():
shared.gradio['Stop'].click(None, None, None, cancels=gen_events) shared.gradio['Stop'].click(None, None, None, cancels=gen_events)
shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}") shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}")
with gr.Tab("LoRA", elem_id="lora"):
with gr.Row():
with gr.Column():
gr.Markdown("Load")
with gr.Row():
shared.gradio['lora_menu'] = gr.Dropdown(choices=available_loras, value=shared.lora_name, label='LoRA')
ui.create_refresh_button(shared.gradio['lora_menu'], lambda : None, lambda : {'choices': get_available_loras()}, 'refresh-button')
with gr.Column():
gr.Markdown("Train (TODO)")
gr.Button("Practice your button clicking skills")
shared.gradio['lora_menu'].change(load_lora_wrapper, [shared.gradio['lora_menu']], [shared.gradio['lora_menu']], show_progress=True)
with gr.Tab("Interface mode", elem_id="interface-mode"): with gr.Tab("Interface mode", elem_id="interface-mode"):
modes = ["default", "notebook", "chat", "cai_chat"] modes = ["default", "notebook", "chat", "cai_chat"]
current_mode = "default" current_mode = "default"