Text Classification
Transformers
ONNX
Safetensors
modernbert
semantic-router
vela
text-embeddings-inference
Instructions to use vllm-sr/Vela-1.0-Encoder-307M-Modality 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-Modality 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-Modality")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vllm-sr/Vela-1.0-Encoder-307M-Modality") model = AutoModelForSequenceClassification.from_pretrained("vllm-sr/Vela-1.0-Encoder-307M-Modality", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download modality_mapping.json from vllm-sr/Vela-1.0-Encoder-307M-Modality: direct link, hf CLI and curl.
- Browser
- Download file 153 Bytes
-
https://huggingface.co/vllm-sr/Vela-1.0-Encoder-307M-Modality/resolve/main/modality_mapping.json
- Command line
-
hf download hf://vllm-sr/Vela-1.0-Encoder-307M-Modality/modality_mapping.json
-
curl -L -o modality_mapping.json https://huggingface.co/vllm-sr/Vela-1.0-Encoder-307M-Modality/resolve/main/modality_mapping.json
153 Bytes
| { | |
| "label_to_idx": { | |
| "AR": 0, | |
| "BOTH": 2, | |
| "DIFFUSION": 1 | |
| }, | |
| "idx_to_label": { | |
| "0": "AR", | |
| "2": "BOTH", | |
| "1": "DIFFUSION" | |
| } | |
| } | |