| | --- |
| | tags: |
| | - pytorch_model_hub_mixin |
| | - model_hub_mixin |
| | license: gpl-3.0 |
| | --- |
| | |
| | This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: |
| | - Library: [More Information Needed] |
| | - Docs: [More Information Needed] |
| |
|
| | ## Steps to run model |
| | - First install [transforna](https://github.com/gitHBDX/TransfoRNA/tree/master) |
| | - Example code: |
| | ``` |
| | from transforna import GeneEmbeddModel,RnaTokenizer |
| | import torch |
| | model_name = 'Seq-Struct' |
| | model_path = f"HBDX/{model_name}-TransfoRNA" |
| | |
| | #load model and tokenizer |
| | model = GeneEmbeddModel.from_pretrained(model_path) |
| | model.eval() |
| | |
| | #init tokenizer. Tokenizer will automatically get secondary structure of sequence using Vienna RNA package |
| | tokenizer = RnaTokenizer.from_pretrained(model_path,model_name=model_name) |
| | output = tokenizer(['AAAGTCGGAGGTTCGAAGACGATCAGATAC','TTTTCGGAACTGAGGCCATGATTAAGAGGG']) |
| | |
| | #inference |
| | #gene_embedds and second input embedds are the latent space representation of the input sequence and the second input respectively. |
| | #In this case, the second input would be the secondary structure of the sequence |
| | gene_embedd, second_input_embedd, activations,attn_scores_first,attn_scores_second = \ |
| | model(output['input_ids']) |
| | |
| | |
| | #get sub class labels |
| | sub_class_labels = model.convert_ids_to_labels(activations) |
| | |
| | #get major class labels |
| | major_class_labels = model.convert_subclass_to_majorclass(sub_class_labels) |
| | |
| | ``` |
| |
|
| |
|
