Instructions to use lfoppiano/MatTPUSciBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lfoppiano/MatTPUSciBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lfoppiano/MatTPUSciBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lfoppiano/MatTPUSciBERT") model = AutoModelForMaskedLM.from_pretrained("lfoppiano/MatTPUSciBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Add HF card metadata; fix duplicate metrics row; polish (#2)
- Add HF card metadata; fix duplicate metrics row; polish (cc5fc645eb8c7e67b65471cf25349d3b15fbe160)47fd0e1
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (22d9a66894da0c1f0d0a1c044a08bf0747fd253e) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>be97273
-
Fix casing
Luca Foppiano9858899
-
update readme
Luca Foppiano7912cbc -
update readme
Luca Foppiano599c490 -
add model_type in config.json
Luca Foppianod46e33e -
cleanup
Luca Foppiano6570f49 -
rename readme
Luca Foppiano1294244 -
improve readme
Luca Foppianoa477d2f -
add model for TF and PT
Luca Foppiano9f41599 -
initial commit
d295f76