Instructions to use HelpingAI/HAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HelpingAI/HAI with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HelpingAI/HAI") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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### Features:
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- **Input Dimensionality:** Handles up to 256 tokens per input.
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- **Output Dimensionality:** 384-dimensional dense embeddings.
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- **Similarity Metric:** Cosine Similarity, fine-tuned for nuanced semantic and emotional comparisons.
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### Full Architecture
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```python
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### Features:
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- **Input Dimensionality:** Handles up to 256 tokens per input.
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- **Output Dimensionality:** 384-dimensional dense embeddings.
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### Full Architecture
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```python
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