Text Classification
Transformers
Safetensors
English
modernbert
evalroute
task-routing
gonogo
text-embeddings-inference
Instructions to use keppy/evalroute-lane-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keppy/evalroute-lane-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keppy/evalroute-lane-encoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("keppy/evalroute-lane-encoder") model = AutoModelForSequenceClassification.from_pretrained("keppy/evalroute-lane-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download split.json from keppy/evalroute-lane-encoder: direct link, hf CLI and curl.
- Browser
- Download file 9.96 kB
-
https://huggingface.co/keppy/evalroute-lane-encoder/resolve/main/split.json
- Command line
-
hf download hf://keppy/evalroute-lane-encoder/split.json
-
curl -L -o split.json https://huggingface.co/keppy/evalroute-lane-encoder/resolve/main/split.json
9.96 kB
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