Instructions to use abdullah/microsoft-deberta-v3-small-1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdullah/microsoft-deberta-v3-small-1024 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="abdullah/microsoft-deberta-v3-small-1024")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("abdullah/microsoft-deberta-v3-small-1024") model = AutoModelForTokenClassification.from_pretrained("abdullah/microsoft-deberta-v3-small-1024", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ad14748c8255e74cb7771ac4870585eedb584dae3ede80132fe9400f2f6b117
- Size of remote file:
- 4.92 kB
- SHA256:
- f68f2aa7515d1357ac07ac15594d6a37c56e7ea26001ec7cfe7b3b3c52ea4aab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.