Instructions to use zhihan1996/DNA_bert_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zhihan1996/DNA_bert_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="zhihan1996/DNA_bert_4", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("zhihan1996/DNA_bert_4", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("zhihan1996/DNA_bert_4", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zhihan1996/DNA_bert_4: direct link, hf CLI and curl.
- Browser
- Download file 347 MB
-
https://huggingface.co/zhihan1996/DNA_bert_4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://zhihan1996/DNA_bert_4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zhihan1996/DNA_bert_4/resolve/main/pytorch_model.bin
347 MB
- Xet hash:
- ea031f3cbb96f443dc215c30df2078c5c78cb19de7e760b81b47f41a60fe2e37
- Size of remote file:
- 347 MB
- SHA256:
- c2914d5fe6ab35d7981d92f4eb9382e87d7caf20d0573651cdf82d5b0daf2d00
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