Instructions to use geninhu/roberta_large_ITPT_FP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use geninhu/roberta_large_ITPT_FP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="geninhu/roberta_large_ITPT_FP")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("geninhu/roberta_large_ITPT_FP") model = AutoModelForMaskedLM.from_pretrained("geninhu/roberta_large_ITPT_FP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from geninhu/roberta_large_ITPT_FP: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/geninhu/roberta_large_ITPT_FP/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://geninhu/roberta_large_ITPT_FP/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/geninhu/roberta_large_ITPT_FP/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- aedb26629d03655dad443e1d57433276efe102759429b64af411cc63e3f88e3b
- Size of remote file:
- 1.42 GB
- SHA256:
- 95aba5302b3e5b8be84cd199daec731e737db0269fddfb79e21147a12ef16fbd
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