Instructions to use InstaDeepAI/nucleotide-transformer-2.5b-multi-species with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/nucleotide-transformer-2.5b-multi-species with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="InstaDeepAI/nucleotide-transformer-2.5b-multi-species")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("InstaDeepAI/nucleotide-transformer-2.5b-multi-species") model = AutoModelForMaskedLM.from_pretrained("InstaDeepAI/nucleotide-transformer-2.5b-multi-species") - Notebooks
- Google Colab
- Kaggle
Add TF weights
#2
by Rocketknight1 HF Staff - opened
Model converted by the transformers' pt_to_tf CLI. All converted model outputs and hidden layers were validated against its PyTorch counterpart.
Maximum crossload output difference=1.007e-03; Maximum crossload hidden layer difference=9.155e-04;
Maximum conversion output difference=1.007e-03; Maximum conversion hidden layer difference=9.155e-04;
CAUTION: The maximum admissible error was manually increased to 0.0011!
tpierrot changed pull request status to merged