Instructions to use SzegedAI/bert-small_20M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SzegedAI/bert-small_20M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SzegedAI/bert-small_20M")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SzegedAI/bert-small_20M") model = AutoModelForMaskedLM.from_pretrained("SzegedAI/bert-small_20M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SzegedAI/bert-small_20M: direct link, hf CLI and curl.
- Browser
- Download file 112 MB
-
https://huggingface.co/SzegedAI/bert-small_20M/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SzegedAI/bert-small_20M/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SzegedAI/bert-small_20M/resolve/main/pytorch_model.bin
112 MB
- Xet hash:
- b8314ff6d56326be1cf8366684690ac46b4d5d61cfa7183d4d6ee3ded261f4a6
- Size of remote file:
- 112 MB
- SHA256:
- 4fbeeeb8edf1a1d1f5dac9d0289b3c8e5c842a79b827518a70e825a0ce8a2c8a
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