Feature Extraction
Transformers
Safetensors
sentence-transformers
embeddings
lora
sociology
retrieval
Instructions to use CodeSoulco/THETA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeSoulco/THETA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="CodeSoulco/THETA")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CodeSoulco/THETA", dtype="auto") - sentence-transformers
How to use CodeSoulco/THETA with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("CodeSoulco/THETA") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
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@@ -131,7 +131,7 @@ If you use this model in your research, please cite:
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```bibtex
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@misc{theta2026,
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title={THETA:
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author={CodeSoul},
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year={2026},
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publisher={Hugging Face},
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```bibtex
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@misc{theta2026,
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title={THETA: Textual Hybrid Embedding–based Topic Analysis},
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author={CodeSoul},
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year={2026},
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publisher={Hugging Face},
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