Instructions to use hf-tiny-model-private/tiny-random-EsmForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-EsmForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-EsmForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-EsmForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-EsmForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 131 Bytes
b5fa453 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:4d3d53e0f95354fda57f28e4019c53152c6ad3b7913c39d5b64f9b3e46d43fd5
size 238396
|