Text Classification
Transformers
Safetensors
English
modernbert
legal
document-ai
page-classification
text-embeddings-inference
Instructions to use RayJackson30/clawbert-149 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RayJackson30/clawbert-149 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RayJackson30/clawbert-149")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RayJackson30/clawbert-149") model = AutoModelForSequenceClassification.from_pretrained("RayJackson30/clawbert-149", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35f51efe2d2de2f32ec0d9ae00b6004de2af3e0805a716fe14b15a14cee6f1b5
- Size of remote file:
- 7.13 MB
- SHA256:
- 5e4cf5e8f820e0c45361960e1160014f1c2e4e8d7f0315646f7d8e34d482b05f
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