Instructions to use Rustem/roberta-base-trained-43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rustem/roberta-base-trained-43 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rustem/roberta-base-trained-43")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Rustem/roberta-base-trained-43") model = AutoModelForMaskedLM.from_pretrained("Rustem/roberta-base-trained-43", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Rustem/roberta-base-trained-43: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Rustem/roberta-base-trained-43/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Rustem/roberta-base-trained-43/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Rustem/roberta-base-trained-43/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 6ca04f6ce91f6c1e7bbcfb92d3b5b63f6a0f3f8ec1c1927d95c8298ea9b9be53
- Size of remote file:
- 499 MB
- SHA256:
- 7c261450e46d84951af6a3dc4182fe738232f232b3f528e2ef010b6f84e2828c
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