Instructions to use malteos/arqmath-bert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malteos/arqmath-bert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="malteos/arqmath-bert-base-cased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("malteos/arqmath-bert-base-cased") model = AutoModelForSequenceClassification.from_pretrained("malteos/arqmath-bert-base-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from malteos/arqmath-bert-base-cased: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/malteos/arqmath-bert-base-cased/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://malteos/arqmath-bert-base-cased/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/malteos/arqmath-bert-base-cased/resolve/main/flax_model.msgpack
433 MB
- Xet hash:
- 8881e86db1cf061a566d1d86f0a0edcd9377753ac620aff4e81cf9b0238cebc9
- Size of remote file:
- 433 MB
- SHA256:
- 005e673f5728db1cc0d4e6952afd7d5640235108a5999a147edf6327269913b9
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