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
Delete embeddings/4B/supervised/socialTwitter_supervised_labels.npy with huggingface_hub
Browse files
embeddings/4B/supervised/socialTwitter_supervised_labels.npy
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