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
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d786cbd6a666a3c10b9e7da721aac6678ef9e08b0fd2b11b560b59b41d4d81f6
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size 497791936
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