mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-23 08:28:21 +01:00
84 lines
2.3 KiB
Python
84 lines
2.3 KiB
Python
from modules import shared
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from modules.logging_colors import logger
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from modules.LoRA import add_lora_to_model
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from modules.models import load_model, unload_model
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from modules.models_settings import get_model_metadata, update_model_parameters
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from modules.utils import get_available_loras, get_available_models
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def get_current_model_info():
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return {
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'model_name': shared.model_name,
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'lora_names': shared.lora_names,
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'loader': shared.args.loader
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}
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def list_models():
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return {'model_names': get_available_models()[1:]}
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def list_dummy_models():
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result = {
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"object": "list",
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"data": []
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}
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models = get_available_models()[1:]
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# these are expected by so much, so include some here as a dummy
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for model in ['gpt-3.5-turbo', 'text-embedding-ada-002']:
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result["data"].append(model_info_dict(model))
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for model in models:
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result["data"].append(model_info_dict(model))
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return result
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def model_info_dict(model_name: str) -> dict:
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return {
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"id": model_name,
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"object": "model",
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"created": 0,
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"owned_by": "user"
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}
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def _load_model(data):
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model_name = data["model_name"]
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args = data.get("args", None)
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settings = data.get("settings", None)
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unload_model()
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model_settings = get_model_metadata(model_name)
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update_model_parameters(model_settings)
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# Update shared.args with custom model loading settings
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if args:
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for k in args:
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if hasattr(shared.args, k):
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setattr(shared.args, k, args[k])
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shared.model, shared.tokenizer = load_model(model_name)
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# Update shared.settings with custom generation defaults
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if settings:
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for k in settings:
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if k in shared.settings:
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shared.settings[k] = settings[k]
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if k == 'truncation_length':
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logger.info(f"TRUNCATION LENGTH (UPDATED): {shared.settings['truncation_length']}")
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elif k == 'instruction_template':
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logger.info(f"INSTRUCTION TEMPLATE (UPDATED): {shared.settings['instruction_template']}")
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def list_loras():
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return {'lora_names': get_available_loras()[1:]}
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def load_loras(lora_names):
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add_lora_to_model(lora_names)
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def unload_all_loras():
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add_lora_to_model([])
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