Instructions to use Konstantinos/BERTaTweetGR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Konstantinos/BERTaTweetGR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Konstantinos/BERTaTweetGR")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Konstantinos/BERTaTweetGR") model = AutoModelForMaskedLM.from_pretrained("Konstantinos/BERTaTweetGR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from Konstantinos/BERTaTweetGR: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/Konstantinos/BERTaTweetGR/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Konstantinos/BERTaTweetGR/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Konstantinos/BERTaTweetGR/resolve/main/flax_model.msgpack
334 MB
- Xet hash:
- 7f9597fc387ee54e166e736c0e2008b4c8bdc465b3f70248ebd2a4f08835f666
- Size of remote file:
- 334 MB
- SHA256:
- 95b3b846d2252cd98ce956da69ff6536880090790f5b53240b0876a72d60c717
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