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
| {"labels": ["body", "cover_page", "subsequent_cover_page", "toc", "toa", "exhibit_cover", "proof_of_service", "verification", "judicial_form", "unknown_other", "transcript"], "emb_dim": 768, "d_model": 256, "heads": 4, "layers": 2, "encoder": "model_modernbert_11 (mean-pooled)", "maxlen": 1536} |