Instructions to use InstaDeepAI/nucleotide-transformer-v2-50m-3mer-multi-species with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/nucleotide-transformer-v2-50m-3mer-multi-species with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="InstaDeepAI/nucleotide-transformer-v2-50m-3mer-multi-species", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("InstaDeepAI/nucleotide-transformer-v2-50m-3mer-multi-species", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("InstaDeepAI/nucleotide-transformer-v2-50m-3mer-multi-species", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- adee59c59ae6fc1220feb9913f28df987e97ed94fb2bc8ca450ca2c88d1a7c70
- Size of remote file:
- 207 MB
- SHA256:
- df558322bba2e3eb9d4ef0ad0b763c2d6578f7fb05e5d19358fe7a30ce1bef61
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.