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