Feature Extraction
Transformers
Safetensors
flash_transformer
biology
genomics
long-context
custom_code
Instructions to use isyslab/DNAFlash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use isyslab/DNAFlash with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="isyslab/DNAFlash", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("isyslab/DNAFlash", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 687 Bytes
cad4384 e881592 cad4384 | 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 26 | {
"architectures": [
"FLASHTransformerForPretrained"
],
"auto_map": {
"AutoConfig": "dnaflash.FLASHTransformerConfig",
"AutoModel": "dnaflash.FLASHTransformerForPretrained",
"AutoModelForSequenceClassification": "dnaflash.FLASHTransformerForSequenceClassification"
},
"attn_dropout": 0.0,
"causal": false,
"expansion_factor": 2.0,
"group_size": 256,
"hidden_size": 1024,
"laplace_attn_fn": false,
"model_type": "flash_transformer",
"norm_type": "scalenorm",
"num_layers": 36,
"query_key_dim": 128,
"reduce_group_non_causal_attn": true,
"shift_tokens": true,
"torch_dtype": "float32",
"transformers_version": "4.39.3",
"vocab_size": 4096
}
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