How to use utahnlp/tevatron-elastic-bert-reranker-depth with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="utahnlp/tevatron-elastic-bert-reranker-depth")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("utahnlp/tevatron-elastic-bert-reranker-depth") model = AutoModel.from_pretrained("utahnlp/tevatron-elastic-bert-reranker-depth", device_map="auto")
https://huggingface.co/utahnlp/tevatron-elastic-bert-reranker-depth/resolve/main/tokenizer.json
hf download hf://utahnlp/tevatron-elastic-bert-reranker-depth/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/utahnlp/tevatron-elastic-bert-reranker-depth/resolve/main/tokenizer.json
