Fill-Mask
Transformers
PyTorch
Safetensors
English
bert
arXiv
astrophysics
conceptual analysis
epistemic change
high-energy physics (HEP)
history of science
semantic shift detection
sociology of science
philosophy of science
physics
word embeddings
Instructions to use arnosimons/astro-hep-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arnosimons/astro-hep-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="arnosimons/astro-hep-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("arnosimons/astro-hep-bert") model = AutoModelForMaskedLM.from_pretrained("arnosimons/astro-hep-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from arnosimons/astro-hep-bert: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/arnosimons/astro-hep-bert/resolve/main/tokenizer.json
- Command line
-
hf download hf://arnosimons/astro-hep-bert/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/arnosimons/astro-hep-bert/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.