Instructions to use laugustyniak/roberta-polish-web-embedding-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use laugustyniak/roberta-polish-web-embedding-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="laugustyniak/roberta-polish-web-embedding-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("laugustyniak/roberta-polish-web-embedding-v1") model = AutoModelForMaskedLM.from_pretrained("laugustyniak/roberta-polish-web-embedding-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cd0b5ee208a990adb930333c362f6497acb98058c20b740c5ddb6924fa1f0fb
- Size of remote file:
- 502 MB
- SHA256:
- 2c47856e0cb6c5066a5dd3376443241f15e15f80a9aa8137f2764fc1211e1d32
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.