This is an implementation of Flash Attention 3 CUDA kernels with support for attention sinks. The attention sinks implementation was contributed to Flash Attention by the
vLLM team
. The
transformers team
packaged the implementation and pre-built it for use with the
kernels library
.
How to Use
When loading your model with transformers, provide this repository id as the source of the attention implementation:
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "<your model id on the Hub>"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
device_map="auto",
torch_dtype="auto",
+ # Flash Attention with Sinks+ attn_implementation="kernels-community/vllm-flash-attn3”,
)
This will automatically resolve and download the appropriate code for your architecture. See more details in
this post
.
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kernels-community vllm-flash-attn3 online free url in huggingface.co:
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