Instructions to use radna/Triton-InternViT-6B-448px-V1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radna/Triton-InternViT-6B-448px-V1-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="radna/Triton-InternViT-6B-448px-V1-5", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("radna/Triton-InternViT-6B-448px-V1-5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update flash_attention.py
Browse files- flash_attention.py +1 -1
flash_attention.py
CHANGED
|
@@ -3,7 +3,7 @@ import torch.nn as nn
|
|
| 3 |
from einops import rearrange
|
| 4 |
|
| 5 |
|
| 6 |
-
from
|
| 7 |
from triton_bert_padding import pad_input, unpad_input
|
| 8 |
|
| 9 |
|
|
|
|
| 3 |
from einops import rearrange
|
| 4 |
|
| 5 |
|
| 6 |
+
from triton_flash_atn import _attention
|
| 7 |
from triton_bert_padding import pad_input, unpad_input
|
| 8 |
|
| 9 |
|