Instructions to use InstaDeepAI/nucleotide-transformer-500m-human-ref with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/nucleotide-transformer-500m-human-ref with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="InstaDeepAI/nucleotide-transformer-500m-human-ref")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("InstaDeepAI/nucleotide-transformer-500m-human-ref") model = AutoModelForMaskedLM.from_pretrained("InstaDeepAI/nucleotide-transformer-500m-human-ref") - Inference
- 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=2.575e-05; Maximum crossload hidden layer difference=6.104e-05;
Maximum conversion output difference=2.575e-05; Maximum conversion hidden layer difference=6.104e-05;
CAUTION: The maximum admissible error was manually increased to 7e-05!
tpierrot changed pull request status to merged