Instructions to use hf-internal-testing/tiny-random-Data2VecTextForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecTextForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-Data2VecTextForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 131 Bytes
9111a44 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:13756bee4b9717e9ac3c555328199232c073b57ed885a74c1df6f148f92022b2
size 466386
|