Instructions to use neurocode/IsRoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neurocode/IsRoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="neurocode/IsRoBERTa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("neurocode/IsRoBERTa") model = AutoModelForMaskedLM.from_pretrained("neurocode/IsRoBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from neurocode/IsRoBERTa: direct link, hf CLI and curl.
- Browser
- Download file 1.78 kB
-
https://huggingface.co/neurocode/IsRoBERTa/resolve/main/training_args.bin
- Command line
-
hf download hf://neurocode/IsRoBERTa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/neurocode/IsRoBERTa/resolve/main/training_args.bin
1.78 kB
- Xet hash:
- 4aeec70b8913fb8820b94987b88217ee31485fb74cc15af68c525be0c70ed572
- Size of remote file:
- 1.78 kB
- SHA256:
- 616553044560c6d8e02c4d3bac8124b5618f1dd94c2c07f374aa7febf2fdab59
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.