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")# 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
- Xet hash:
- 1e222ab4e9f3d75f6e333efde2781708405281d02e0216872336f4a7a9d05c97
- Size of remote file:
- 438 MB
- SHA256:
- 64f29b5766077b73c6e8ec505322249022850503f8082446e10827e81c919567
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