Feature Extraction
Transformers
ONNX
Safetensors
English
bert
retrieval
constbert
colbert
multi-vector
embedding
custom_code
text-embeddings-inference
Instructions to use anubhavg97/constbert-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anubhavg97/constbert-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="anubhavg97/constbert-onnx", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("anubhavg97/constbert-onnx", trust_remote_code=True) model = AutoModel.from_pretrained("anubhavg97/constbert-onnx", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
updated requirements.txt
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requirements.txt
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torch # Required by your modeling.py for ConstBERT logic
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