Instructions to use AllenGeng/OCamlBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AllenGeng/OCamlBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AllenGeng/OCamlBert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AllenGeng/OCamlBert") model = AutoModelForMaskedLM.from_pretrained("AllenGeng/OCamlBert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AllenGeng/OCamlBert: direct link, hf CLI and curl.
- Browser
- Download file 3.25 kB
-
https://huggingface.co/AllenGeng/OCamlBert/resolve/main/training_args.bin
- Command line
-
hf download hf://AllenGeng/OCamlBert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AllenGeng/OCamlBert/resolve/main/training_args.bin
3.25 kB
- Xet hash:
- c5aaa7c05eef391c6819e71cef2cd26c9bb4b69fec5bb6bfe806de8488b9e93b
- Size of remote file:
- 3.25 kB
- SHA256:
- 11e3f1fd33b0deaa8613a64fa0bbdaca6b4d40c3e72267bef32e1cb3efe0f909
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