haive.core.models.llm.providers.huggingface¶
HuggingFace Provider Module.
This module implements the HuggingFace language model provider for the Haive framework, supporting both HuggingFace Hub hosted models and local transformer models.
The provider handles API key management (for Hub), model configuration, and safe imports of the langchain-huggingface package dependencies.
Examples
Hub-hosted model:
from haive.core.models.llm.providers.huggingface import HuggingFaceProvider
provider = HuggingFaceProvider(
model="microsoft/DialoGPT-medium",
temperature=0.7,
max_tokens=1000
)
llm = provider.instantiate()
Local transformer model:
provider = HuggingFaceProvider(
model="gpt2",
device_map="auto",
load_in_8bit=True,
temperature=0.8
)
Classes¶
HuggingFace language model provider configuration. |
Module Contents¶
- class haive.core.models.llm.providers.huggingface.HuggingFaceProvider(/, **data)¶
Bases:
haive.core.models.llm.providers.base.BaseLLMProviderHuggingFace language model provider configuration.
This provider supports both HuggingFace Hub hosted models and local transformer models, providing access to thousands of open-source models.
- Parameters:
data (Any)
- provider¶
Always LLMProvider.HUGGINGFACE
- Type:
Examples
Popular conversational model:
provider = HuggingFaceProvider( model="microsoft/DialoGPT-medium", temperature=0.7, max_tokens=1000 )
Local model with quantization:
provider = HuggingFaceProvider( model="meta-llama/Llama-2-7b-chat-hf", load_in_8bit=True, device_map="auto", temperature=0.1 )
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.