Instructions to use korca/roberta-large-lkm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use korca/roberta-large-lkm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="korca/roberta-large-lkm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("korca/roberta-large-lkm") model = AutoModel.from_pretrained("korca/roberta-large-lkm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from korca/roberta-large-lkm: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/korca/roberta-large-lkm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://korca/roberta-large-lkm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/korca/roberta-large-lkm/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- ca821a521ecb764945ba64c4f77cd1ebfdbd0472e7e3d947a17a38a5593413a3
- Size of remote file:
- 1.42 GB
- SHA256:
- cf4d21076fb9ed56511b4423579a47b09bda219a3d21047a4e8ca1d205308a3f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.