How to use imaneb942/MNLP_M3_document_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="imaneb942/MNLP_M3_document_encoder")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("imaneb942/MNLP_M3_document_encoder") model = AutoModel.from_pretrained("imaneb942/MNLP_M3_document_encoder", device_map="auto")
https://huggingface.co/imaneb942/MNLP_M3_document_encoder/resolve/a1771cd4ea6a1061886bd340f8ea4d3fdce60d50/tokenizer.json
hf download hf://imaneb942/MNLP_M3_document_encoder@a1771cd4ea6a1061886bd340f8ea4d3fdce60d50/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/imaneb942/MNLP_M3_document_encoder/resolve/a1771cd4ea6a1061886bd340f8ea4d3fdce60d50/tokenizer.json
