Text Classification
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
sentence-similarity
text-embeddings-inference
Instructions to use randypang/intent-simple-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use randypang/intent-simple-chat with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("randypang/intent-simple-chat") 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] - Transformers
How to use randypang/intent-simple-chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="randypang/intent-simple-chat")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("randypang/intent-simple-chat") model = AutoModel.from_pretrained("randypang/intent-simple-chat") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad10d9c9f4294f40aa26fa03938b54c2be806c200994905316d8d94852256ae8
- Size of remote file:
- 37.8 kB
- SHA256:
- 3bf3f8290c6dda12bd50ee0fa31ce5092caedac9224969876b5fd17bd45008c8
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