Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use orpe42/deberta_MP_dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use orpe42/deberta_MP_dynamic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="orpe42/deberta_MP_dynamic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("orpe42/deberta_MP_dynamic") model = AutoModelForSequenceClassification.from_pretrained("orpe42/deberta_MP_dynamic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from orpe42/deberta_MP_dynamic: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/orpe42/deberta_MP_dynamic/resolve/main/training_args.bin
- Command line
-
hf download hf://orpe42/deberta_MP_dynamic/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/orpe42/deberta_MP_dynamic/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 53428f8456aa9147035dcdbc7a3425da6dc76bd879c8bb3280b7bbb87a8a4341
- Size of remote file:
- 4.86 kB
- SHA256:
- ccb6424b13e2d2b4d4e950b6a79f577097a4d63bf3739f20867425d310e107a2
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