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)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("isyslab/DNAFlash", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -40,7 +40,7 @@ inputs = tokenizer(
|
|
| 40 |
|
| 41 |
# Perform a forward pass through the model to obtain the outputs, including hidden states
|
| 42 |
with torch.inference_mode():
|
| 43 |
-
outputs = model(
|
| 44 |
```
|
| 45 |
|
| 46 |
## Citation
|
|
|
|
| 40 |
|
| 41 |
# Perform a forward pass through the model to obtain the outputs, including hidden states
|
| 42 |
with torch.inference_mode():
|
| 43 |
+
outputs = model(inputs)
|
| 44 |
```
|
| 45 |
|
| 46 |
## Citation
|