Instructions to use hf-internal-testing/tiny-random-ModernBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ModernBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-ModernBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ModernBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-ModernBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -12,6 +12,7 @@ tags: []
|
|
| 12 |
## Model Details
|
| 13 |
### Code to create models
|
| 14 |
```python
|
|
|
|
| 15 |
from transformers import ModernBertConfig, ModernBertForTokenClassification, AutoTokenizer
|
| 16 |
|
| 17 |
model_id = "answerdotai/ModernBERT-base"
|
|
|
|
| 12 |
## Model Details
|
| 13 |
### Code to create models
|
| 14 |
```python
|
| 15 |
+
import torch
|
| 16 |
from transformers import ModernBertConfig, ModernBertForTokenClassification, AutoTokenizer
|
| 17 |
|
| 18 |
model_id = "answerdotai/ModernBERT-base"
|