Instructions to use davidcechak/DNADeberta_finedemo_coding_vs_intergenomic_seqs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidcechak/DNADeberta_finedemo_coding_vs_intergenomic_seqs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davidcechak/DNADeberta_finedemo_coding_vs_intergenomic_seqs")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davidcechak/DNADeberta_finedemo_coding_vs_intergenomic_seqs") model = AutoModelForSequenceClassification.from_pretrained("davidcechak/DNADeberta_finedemo_coding_vs_intergenomic_seqs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from davidcechak/DNADeberta_finedemo_coding_vs_intergenomic_seqs: direct link, hf CLI and curl.
- Browser
- Download file 357 MB
-
https://huggingface.co/davidcechak/DNADeberta_finedemo_coding_vs_intergenomic_seqs/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://davidcechak/DNADeberta_finedemo_coding_vs_intergenomic_seqs@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/davidcechak/DNADeberta_finedemo_coding_vs_intergenomic_seqs/resolve/refs%2Fpr%2F1/pytorch_model.bin
357 MB
- Xet hash:
- 789c75637637235eaeb59a0e530192cf2e8f510b9436fb3c58850185e816f73c
- Size of remote file:
- 357 MB
- SHA256:
- 2fafdaedd8dedaab07918508ec9bacb8ca0cdedde318e421b3edc1aa6220e222
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