Fill-Mask
Transformers
PyTorch
Safetensors
Fairseq
Hebrew
roberta
hebrew
encoder
masked-language-modeling
mlm
named-entity-recognition
sentiment-analysis
monolingual
byte-level-bpe
Instructions to use HalleluBERT/HalleluBERT_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HalleluBERT/HalleluBERT_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HalleluBERT/HalleluBERT_base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HalleluBERT/HalleluBERT_base") model = AutoModelForMaskedLM.from_pretrained("HalleluBERT/HalleluBERT_base") - Fairseq
How to use HalleluBERT/HalleluBERT_base with Fairseq:
from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub models, cfg, task = load_model_ensemble_and_task_from_hf_hub( "HalleluBERT/HalleluBERT_base" ) - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to pytorch_model.bin but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.
rjschmitt changed pull request status to merged