Feature Extraction
Transformers
Safetensors
English
roberta
recommendation
information retrieval
Amazon Reviews 2023
text-embeddings-inference
Instructions to use hyp1231/blair-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hyp1231/blair-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hyp1231/blair-roberta-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hyp1231/blair-roberta-large") model = AutoModel.from_pretrained("hyp1231/blair-roberta-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hyp1231/blair-roberta-large: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/hyp1231/blair-roberta-large/resolve/main/tokenizer.json
- Command line
-
hf download hf://hyp1231/blair-roberta-large/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/hyp1231/blair-roberta-large/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.