from langchain_huggingface import HuggingFacePipeline | |
# Define the model ID | |
model_id = "gpt2" | |
model_id = "microsoft/Phi-4-mini-instruct" | |
model_id = "Qwen/Qwen2.5-7B-Instruct" | |
model_id = "microsoft/Phi-3-small-8k-instruct" | |
# Create a pipeline for text generation | |
llm = HuggingFacePipeline.from_model_id( | |
model_id=model_id, | |
task="text-generation", | |
device=-1, | |
# trust_remote_code=True, | |
pipeline_kwargs={ | |
"max_new_tokens": 256, | |
"top_k": 50 | |
}, | |
) | |
# Use the model to generate text | |
response = llm.invoke("Hello, how are you?") | |
print(response) |