ChatHuggingFace

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Node Details

• Name: ChatHuggingFace
• Type: ChatHuggingFace
• Version: 3.0
• Category: Chat Models

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Base Classes

• ChatHuggingFace
• BaseChatModel
• HuggingFaceInference (and its base classes)

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Parameters

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Credential (Required)

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Parameters

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Credential (Required)

• Type: huggingFaceApi

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Inputs

1. Model (Required)

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Inputs

1. Model (Required)
   • Type: string
   • Description: The name of the HuggingFace model to use (e.g., “gpt2”)
   • Note: Leave blank if using a custom inference endpoint
2. Cache (Optional)
3. Cache (Optional)
   • Type: BaseCache
   • Description: Caching mechanism for the model
4. Endpoint (Optional)
5. Endpoint (Optional)
   • Type: string
   • Description: Custom inference endpoint URL
   • Example: https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/gpt2
6. Temperature (Optional)
7. Temperature (Optional)
   • Type: number
   • Description: Controls randomness in output generation
   • Step: 0.1
8. Max Tokens (Optional)
9. Max Tokens (Optional)
   • Type: number
   • Description: Maximum number of tokens to generate
   • Step: 1
10. Top Probability (Top P) (Optional)
11. Top Probability (Top P) (Optional)
    • Type: number
    • Description: Nucleus sampling parameter
    • Step: 0.1
12. Top K (Optional)
13. Top K (Optional)
    • Type: number
    • Description: Top-K sampling parameter
    • Step: 0.1
14. Frequency Penalty (Optional)
15. Frequency Penalty (Optional)
    • Type: number
    • Description: Penalizes frequent token usage
    • Step: 0.1
16. Stop Sequence (Optional)
17. Stop Sequence (Optional)
    • Type: string
    • Description: Comma-separated list of sequences to stop generation

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Initialization

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Usage

1. Integrating HuggingFace models into chat applications
2. Customizing language model behavior for specific use cases
3. Experimenting with different model parameters
4. Using custom-trained or fine-tuned models via custom endpoints

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Notes

• Some parameters may not apply to all models. Users should check the specific model’s documentation for compatible parameters.
• The node supports both HuggingFace’s hosted models and custom inference endpoints, providing flexibility in deployment options.