Text Classification
Transformers
Safetensors
lfm2
feature-extraction
betterwright
accessibility
browser-agent
reranking
long-context
custom_code
Instructions to use ProCreations/betterwright-encoder-350m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProCreations/betterwright-encoder-350m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProCreations/betterwright-encoder-350m", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ProCreations/betterwright-encoder-350m", trust_remote_code=True) model = AutoModel.from_pretrained("ProCreations/betterwright-encoder-350m", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval.json from ProCreations/betterwright-encoder-350m: direct link, hf CLI and curl.
- Browser
- Download file 506 kB
-
https://huggingface.co/ProCreations/betterwright-encoder-350m/resolve/main/eval.json
- Command line
-
hf download hf://ProCreations/betterwright-encoder-350m/eval.json
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curl -L -o eval.json https://huggingface.co/ProCreations/betterwright-encoder-350m/resolve/main/eval.json
506 kB
File too large to display, you can check the raw version instead.