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
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pipeline_tag: text-classification
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tags:
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- sentence-similarity
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- transformers
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license: apache-2.0
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# {MODEL_NAME}
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