Instructions to use djamina/relatives_psr_seq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djamina/relatives_psr_seq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="djamina/relatives_psr_seq")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("djamina/relatives_psr_seq") model = AutoModelForTokenClassification.from_pretrained("djamina/relatives_psr_seq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from djamina/relatives_psr_seq: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/djamina/relatives_psr_seq/resolve/main/training_args.bin
- Command line
-
hf download hf://djamina/relatives_psr_seq/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/djamina/relatives_psr_seq/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- a2e152f786a89b9b29e9f48414404bba307472d2f06f726f5e9a928ae5c84cbe
- Size of remote file:
- 5.11 kB
- SHA256:
- 0663de823692a0fce5fce313fb6d8a91f3419773b1b568a370170a40090f2ef7
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