Feature Extraction
Transformers
PyTorch
English
modernbert
fill-mask
encoder
text-embeddings-inference
Instructions to use jhu-clsp/ettin-encoder-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhu-clsp/ettin-encoder-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jhu-clsp/ettin-encoder-1b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jhu-clsp/ettin-encoder-1b") model = AutoModelForMaskedLM.from_pretrained("jhu-clsp/ettin-encoder-1b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jhu-clsp/ettin-encoder-1b: direct link, hf CLI and curl.
- Browser
- Download file 4.13 GB
-
https://huggingface.co/jhu-clsp/ettin-encoder-1b/resolve/5e5ccd59e45ed5de7963cc3bd3c6f7c1a4c26314/pytorch_model.bin
- Command line
-
hf download hf://jhu-clsp/ettin-encoder-1b@5e5ccd59e45ed5de7963cc3bd3c6f7c1a4c26314/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jhu-clsp/ettin-encoder-1b/resolve/5e5ccd59e45ed5de7963cc3bd3c6f7c1a4c26314/pytorch_model.bin
4.13 GB
- Xet hash:
- e0b7f439fad32b75b12ecc6c2a134a7fb26f1cae105668881b87815841beeefd
- Size of remote file:
- 4.13 GB
- SHA256:
- 3f870c3a28b7020a9a5948b9bc10822521aae0c0bf5c95820b7b27581bce6f39
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