Instructions to use vr25/fin_BERT-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vr25/fin_BERT-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vr25/fin_BERT-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vr25/fin_BERT-v1") model = AutoModelForMaskedLM.from_pretrained("vr25/fin_BERT-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from vr25/fin_BERT-v1: direct link, hf CLI and curl.
- Browser
- Download file 348 MB
-
https://huggingface.co/vr25/fin_BERT-v1/resolve/main/optimizer.pt
- Command line
-
hf download hf://vr25/fin_BERT-v1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/vr25/fin_BERT-v1/resolve/main/optimizer.pt
348 MB
- Xet hash:
- 83378f1251c6942234a0329f4f4d40ac711c043e004b2a440c795a32b5eb2cc5
- Size of remote file:
- 348 MB
- SHA256:
- 2a585c2978665886c9d14b97e6bdcf3eac7e3801415881afc9767fe9079704e4
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