Feature Extraction
Transformers
Joblib
Safetensors
BulkRNABert
bulk RNA-seq
biology
transcriptomics
custom_code
Instructions to use InstaDeepAI/BulkRNABert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/BulkRNABert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="InstaDeepAI/BulkRNABert", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("InstaDeepAI/BulkRNABert", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 575 Bytes
1b644d1 acefdf1 1b644d1 acefdf1 1b644d1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"architectures": [
"BulkRNABert"
],
"attention_maps_to_save": [],
"auto_map": {
"AutoConfig": "bulkrnabert.BulkRNABertConfig",
"AutoModel": "bulkrnabert.BulkRNABert"
},
"embed_dim": 256,
"embeddings_layers_to_save": [],
"ffn_embed_dim": 512,
"init_gene_embed_dim": 200,
"key_size": 32,
"model_type": "BulkRNABert",
"n_expressions_bins": 66,
"n_genes": 19062,
"num_attention_heads": 8,
"num_layers": 4,
"project_gene_embedding": true,
"torch_dtype": "float32",
"transformers_version": "4.51.0",
"use_gene_embedding": true
}
|