wehub-resource-sync
58 lines
2.7 KiB
Python
58 lines
2.7 KiB
Python
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""" This example shows how to use Qwen2 models in LLMWare, consisting of three main categories -
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1 - standard QWEN2 chat/instruct models, packaged in GGUF in 7B / 1.5B / 0.5B sizes.
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2 - RAG fine-tuned QWEN2 in DRAGON and BLING series.
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3 - Extract function-calling finetune in SLIM series.
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"""
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from llmware.models import ModelCatalog
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# 1 - MAIN CATALOG - 3 QWEN2 GGUF models for chat (7B / 1.5B / 0.5B)
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qwen2_base_gguf = ["qwen2-7b-instruct-gguf", "qwen2-1.5b-instruct-gguf", "qwen2-0.5b-instruct-gguf"]
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print("\nExample #1 - loading Qwen2-instruct model - may take a minute the first time.")
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qwen2 = ModelCatalog().load_model("qwen2-1.5b-instruct-gguf", max_output=200)
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response = qwen2.inference("I am going to visit Istanbul. What should I see?")
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print("\nresponse: ", response)
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# 2 - RAG FINETUNE - DRAGON + BLING
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print("\nExample #2 - RAG finetuned Qwen2 for fact-based question answering with context passage.")
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qwen2_rag_finetunes = ["dragon-qwen-7b-gguf", "bling-qwen-1.5b-gguf", "bling-qwen-0.5b-gguf"]
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qwen2_rag = ModelCatalog().load_model("bling-qwen-1.5b-gguf", temperature=0.0, sample=False)
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context = "The stock is now soaring to $120 per share after great earnings."
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response = qwen2_rag.inference("What is the current stock price?", add_context=context)
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print("\nqwen2-rag response: ", response)
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# 3 - FUNCTION-CALLING EXTRACTION SLIM MODELS
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print("\nExample #3 - Qwen2 Extract function calling model.")
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qwen2_extract_function_calls = ["slim-extract-qwen-1.5b-gguf", "slim-extract-qwen-0.5b-gguf"]
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context_passage = ("Adobe shares tumbled as much as 11% in extended trading Thursday after the design software maker "
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"issued strong fiscal first-quarter results but came up slightly short on quarterly revenue guidance. "
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"Here’s how the company did, compared with estimates from analysts polled by LSEG, formerly known as Refinitiv: "
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"Earnings per share: $4.48 adjusted vs. $4.38 expected Revenue: $5.18 billion vs. $5.14 billion expected "
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"Adobe’s revenue grew 11% year over year in the quarter, which ended March 1, according to a statement. "
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"Net income decreased to $620 million, or $1.36 per share, from $1.25 billion, or $2.71 per share, "
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"in the same quarter a year ago. During the quarter, Adobe abandoned its $20 billion acquisition of "
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"design software startup Figma after U.K. regulators found competitive concerns. The company paid "
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"Figma a $1 billion termination fee.")
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qwen2_extract = ModelCatalog().load_model("slim-extract-qwen-1.5b-gguf",temperature=0.0,sample=False)
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response = qwen2_extract.function_call(context_passage, params=["earnings per share"])
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print("\nqwen2-extract response: ", response)
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