Instructions to use FremyCompany/rl-bert-oscar-nl-step4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FremyCompany/rl-bert-oscar-nl-step4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FremyCompany/rl-bert-oscar-nl-step4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FremyCompany/rl-bert-oscar-nl-step4") model = AutoModelForMaskedLM.from_pretrained("FremyCompany/rl-bert-oscar-nl-step4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from FremyCompany/rl-bert-oscar-nl-step4: direct link, hf CLI and curl.
- Browser
- Download file 1.38 GB
-
https://huggingface.co/FremyCompany/rl-bert-oscar-nl-step4/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://FremyCompany/rl-bert-oscar-nl-step4@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FremyCompany/rl-bert-oscar-nl-step4/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.38 GB
- Xet hash:
- c76235162d87429d22fb9132ef15f5d2d8b41418a3b2b04a6b37d9c6097c2eb4
- Size of remote file:
- 1.38 GB
- SHA256:
- fcaf1bb11f5ec7ed1a79ea30c9d8e5a8452dd4481720437236425a6a36ae27d9
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