Instructions to use ccdv/lsg-distilroberta-base-4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ccdv/lsg-distilroberta-base-4096 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ccdv/lsg-distilroberta-base-4096", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ccdv/lsg-distilroberta-base-4096", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("ccdv/lsg-distilroberta-base-4096", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ccdv/lsg-distilroberta-base-4096: direct link, hf CLI and curl.
- Browser
- Download file 341 MB
-
https://huggingface.co/ccdv/lsg-distilroberta-base-4096/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ccdv/lsg-distilroberta-base-4096/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ccdv/lsg-distilroberta-base-4096/resolve/main/pytorch_model.bin
341 MB
- Xet hash:
- 13f024b4f2d417e47b88681f309e40efb98008a46c6413de09e5a6dfa76fc335
- Size of remote file:
- 341 MB
- SHA256:
- cb84c9d98ba5b4ef47b750c8c5ccce3a788ae4e4ef6e04d0b6ef1b009ccb67a0
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