Token Classification
Transformers
Safetensors
longformer
Generated from Trainer
Eval Results (legacy)
Instructions to use Theoreticallyhugo/longformer-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Theoreticallyhugo/longformer-simple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Theoreticallyhugo/longformer-simple")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Theoreticallyhugo/longformer-simple") model = AutoModelForTokenClassification.from_pretrained("Theoreticallyhugo/longformer-simple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-729/optimizer.pt from Theoreticallyhugo/longformer-simple: direct link, hf CLI and curl.
- Browser
- Download file 1.01 GB
-
https://huggingface.co/Theoreticallyhugo/longformer-simple/resolve/main/checkpoint-729/optimizer.pt
- Command line
-
hf download hf://Theoreticallyhugo/longformer-simple/checkpoint-729/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Theoreticallyhugo/longformer-simple/resolve/main/checkpoint-729/optimizer.pt
1.01 GB
- Xet hash:
- 9ead9de24e1f532fbc2f1de0f11509503d652e3d5d46eb5c721902593a4d8d0a
- Size of remote file:
- 1.01 GB
- SHA256:
- 32a34a1f8f9444a64372b6cae7bba92e7b6440acbe638d9792250ce30aceea02
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.