Text Classification
Transformers
Safetensors
English
bert
rag
retrieval
reranker
calibration
decision-model
cross-encoder
text-embeddings-inference
Instructions to use sdmlai/nano-jev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sdmlai/nano-jev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sdmlai/nano-jev")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sdmlai/nano-jev") model = AutoModelForSequenceClassification.from_pretrained("sdmlai/nano-jev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sdmlai/nano-jev: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/sdmlai/nano-jev/resolve/main/tokenizer.json
- Command line
-
hf download hf://sdmlai/nano-jev/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/sdmlai/nano-jev/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.