Text Classification
Transformers
Safetensors
English
bert
image-optimization
technique-routing
headroom
text-embeddings-inference
Instructions to use chopratejas/technique-router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chopratejas/technique-router with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chopratejas/technique-router")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chopratejas/technique-router") model = AutoModelForSequenceClassification.from_pretrained("chopratejas/technique-router", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
| { | |
| "label2id": { | |
| "transcode": 0, | |
| "crop": 1, | |
| "preserve": 2, | |
| "full_low": 3 | |
| }, | |
| "id2label": { | |
| "0": "transcode", | |
| "1": "crop", | |
| "2": "preserve", | |
| "3": "full_low" | |
| } | |
| } |