Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use kwang123/deberta-large-ReqORNot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kwang123/deberta-large-ReqORNot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kwang123/deberta-large-ReqORNot")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kwang123/deberta-large-ReqORNot") model = AutoModelForSequenceClassification.from_pretrained("kwang123/deberta-large-ReqORNot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kwang123/deberta-large-ReqORNot: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/kwang123/deberta-large-ReqORNot/resolve/main/training_args.bin
- Command line
-
hf download hf://kwang123/deberta-large-ReqORNot/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kwang123/deberta-large-ReqORNot/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 412465b126a16f174abe156b245d2d1d5301a71d5e092b0e13d246810cc381d0
- Size of remote file:
- 4.92 kB
- SHA256:
- eb776d62c12a76067ffa7d0a1c158f788c4b429a9c3f61132dfafc341ebce3ff
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