Instructions to use tharindu/roberta-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tharindu/roberta-50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tharindu/roberta-50")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tharindu/roberta-50") model = AutoModelForMaskedLM.from_pretrained("tharindu/roberta-50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from tharindu/roberta-50: direct link, hf CLI and curl.
- Browser
- Download file 2.84 GB
-
https://huggingface.co/tharindu/roberta-50/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://tharindu/roberta-50@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/tharindu/roberta-50/resolve/refs%2Fpr%2F1/optimizer.pt
2.84 GB
- Xet hash:
- 0df5d0fd40995d586f5967981ad59792195f45404e2e31114ee9dcbca094b67d
- Size of remote file:
- 2.84 GB
- SHA256:
- 36e6068c7cc66d29a860c30acd47d01ff91fd30359b7edc7450e162efcde9f56
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