Feature Extraction
PEFT
Safetensors
embeddings
m6
paper-fulltext-embedding
papers
repository-library
research-library
scientific-papers
t3_paper_text
Instructions to use PeytonT/paper-fulltext-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use PeytonT/paper-fulltext-embedding with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("allenai/scibert_scivocab_uncased") model = PeftModel.from_pretrained(base_model, "PeytonT/paper-fulltext-embedding") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from PeytonT/paper-fulltext-embedding: direct link, hf CLI and curl.
- Browser
- Download file 717 kB
-
https://huggingface.co/PeytonT/paper-fulltext-embedding/resolve/main/tokenizer.json
- Command line
-
hf download hf://PeytonT/paper-fulltext-embedding/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/PeytonT/paper-fulltext-embedding/resolve/main/tokenizer.json
717 kB
File too large to display, you can check the raw version instead.