Text Ranking
Transformers
Safetensors
English
qwen2
text-generation
reranker
retrieval
text-embeddings-inference
Instructions to use jhu-clsp/rank1-14b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhu-clsp/rank1-14b with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jhu-clsp/rank1-14b") model = AutoModelForCausalLM.from_pretrained("jhu-clsp/rank1-14b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12924220b14e6c7ca53fde001e7614c664ad72277378c6c14fc71cf735b0c52e
- Size of remote file:
- 11.4 MB
- SHA256:
- 3bbbede8a5db70ed006fa645af44ebd6a069c667d16bb9e7a0d00a5a6dc7111e
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