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
how can I use this model to forecast enhancers?
Dear Developers,
Thank you for providing such a powerful and meaningful model! As a beginner in Hugging Face, I have been following the official tutorials to familiarize myself with the platform. However, I am currently struggling with how to fine-tune your model using the provided enhancer datasets to predict whether a given sequence is an enhancer.
I understand the basics of Hugging Face and transformer, but I would greatly appreciate detailed guidance on how to:
Utilize your enhancer datasets for fine-tuning the model.
Use the fine-tuned model to make predictions on new sequences.
Any advice or step-by-step instructions would be incredibly helpful. Thank you for your time and for sharing your work with the community!
Best regards,
Nanu
Hello @Nanu4hugging
Look at the section Second task : Enhancer type prediction in this notebook.
Best regards and happy new year!
Thanks for your kind reply! All the best!!!!