wehub-resource-sync
56 lines
1.9 KiB
Python
56 lines
1.9 KiB
Python
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"""This example illustrates the basic capabilities of the Model Catalog and how to use"""
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from llmware.models import ModelCatalog
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from llmware.prompts import Prompt
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# 1 - to list all of the models registered by default in llmware
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mc = ModelCatalog().list_all_models()
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print("\nAll-Models-List")
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for i, models in enumerate(mc):
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print("update: models - ", i, models)
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# 2 - to list all generative local models
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gl_mc = ModelCatalog().list_generative_local_models()
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print("\nGenerative-Local-Models-List")
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for i, models in enumerate(gl_mc):
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print("update: gen local models - ", i, models)
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# 3 - to add models to the catalog, e.g., sentence transformer
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ModelCatalog().register_sentence_transformer_model("all-MiniLM-L6-v2", embedding_dims=384,
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context_window=256)
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"""
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ModelRegistry().add_model_list({"model_name": "all-MiniLM-L6-v2", "model_category": "embedding",
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"embedding_dims":384, "context_window":256, "model_family": "LLMWareSemanticModel",
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"display_name": "MiniLM", "model_location": "st_repo"})
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"""
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# to confirm that model was added
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model_card = ModelCatalog().lookup_model_card("all-MiniLM-L6-v2")
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print("\nupdate: Registered new embedding model - ", model_card)
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# 4 - embedding models
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emb_models = ModelCatalog().list_embedding_models()
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# note: newly created 'all-MiniLM-L6-v2' will now be included
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print("\nEmbedding-Models-List")
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for i, models in enumerate(emb_models):
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print("update: embedding models - ", i, models)
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# 5 - to delete model from catalog
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ModelCatalog().delete_model_card("gpt-3.5-turbo")
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# 6 - to load any model in the catalog
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new_model = ModelCatalog().load_model("all-MiniLM-L6-v2")
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# 7 - equivalent 'load_model' with any prompt
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# -- note: if this model is not installed locally, this will pull it down into local cache
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prompter = Prompt().load_model("llmware/bling-1b-0.1")
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