Text Classification
Transformers
ONNX
Safetensors
modernbert
semantic-router
vela
text-embeddings-inference
Instructions to use vllm-sr/Vela-1.0-Encoder-307M-Domain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vllm-sr/Vela-1.0-Encoder-307M-Domain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vllm-sr/Vela-1.0-Encoder-307M-Domain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vllm-sr/Vela-1.0-Encoder-307M-Domain") model = AutoModelForSequenceClassification.from_pretrained("vllm-sr/Vela-1.0-Encoder-307M-Domain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download category_mapping.json from vllm-sr/Vela-1.0-Encoder-307M-Domain: direct link, hf CLI and curl.
- Browser
- Download file 625 Bytes
-
https://huggingface.co/vllm-sr/Vela-1.0-Encoder-307M-Domain/resolve/main/category_mapping.json
- Command line
-
hf download hf://vllm-sr/Vela-1.0-Encoder-307M-Domain/category_mapping.json
-
curl -L -o category_mapping.json https://huggingface.co/vllm-sr/Vela-1.0-Encoder-307M-Domain/resolve/main/category_mapping.json
625 Bytes
| { | |
| "category_to_idx": { | |
| "biology": 0, | |
| "business": 1, | |
| "chemistry": 2, | |
| "computer science": 3, | |
| "economics": 4, | |
| "engineering": 5, | |
| "health": 6, | |
| "history": 7, | |
| "law": 8, | |
| "math": 9, | |
| "other": 10, | |
| "philosophy": 11, | |
| "physics": 12, | |
| "psychology": 13 | |
| }, | |
| "idx_to_category": { | |
| "0": "biology", | |
| "1": "business", | |
| "2": "chemistry", | |
| "3": "computer science", | |
| "4": "economics", | |
| "5": "engineering", | |
| "6": "health", | |
| "7": "history", | |
| "8": "law", | |
| "9": "math", | |
| "10": "other", | |
| "11": "philosophy", | |
| "12": "physics", | |
| "13": "psychology" | |
| } | |
| } | |