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paolomanlapaz/rispice-base
rispice-base is a machine learning model from paolomanlapaz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
RiSPICE Base is the sequence classification model used by RiSPICE (Rice SNP Prioritization Integrating Chromatin Effects). It is built upon DNABERT-2-117M and provides the multi-label chromatin feature prediction head…
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From the Hugging Face model README
RiSPICE Base is the sequence classification model used by RiSPICE (Rice SNP Prioritization Integrating Chromatin Effects). It is built upon DNABERT-2-117M and provides the multi-label chromatin feature prediction head required for RiSPICE inference. Separate LoRA adapters are provided for each supported sequence length.
zhihan1996/DNABERT-2-117MThis repository is intended to be used together with one of the RiSPICE LoRA adapters:
paolomanlapaz/rispice-1000bppaolomanlapaz/rispice-750bppaolomanlapaz/rispice-500bpThe model outputs logits (or probabilities after applying a sigmoid function) for the following 12 chromatin features, in the exact order shown below:
| Index | Feature |
|---|---|
| 0 | ATAC-Seq |
| 1 | H3K4ac |
| 2 | H3K4me2 |
| 3 | H3K4me3 |
| 4 | H3K9ac |
| 5 | H3K9me1 |
| 6 | H3K23ac |
| 7 | H3K27ac |
| 8 | H3K27me3 |
| 9 | H3K36me3 |
| 10 | H4K12ac |
| 11 | H4K16ac |
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained(
"paolomanlapaz/rispice-base",
trust_remote_code=True,
)
tokenizer = AutoTokenizer.from_pretrained(
"paolomanlapaz/rispice-base",
trust_remote_code=True,
)
After loading the base model, apply the desired RiSPICE LoRA adapter (500 bp, 750 bp, or 1000 bp) before performing inference.
For preprocessing, inference scripts, and documentation, please visit the RiSPICE repository: