huggingface / optimum-nvidia
- суббота, 9 декабря 2023 г. в 00:00:05
Optimum-NVIDIA delivers the best inference performance on the NVIDIA platform through Hugging Face. Run LLaMA 2 at 1,200 tokens/second (up to 28x faster than the framework) by changing just a single line in your existing transformers code.
You can use a Docker container to try Optimum-NVIDIA today. Images are available on the Hugging Face Docker Hub.
docker pull huggingface/optimum-nvidia
An Optimum-NVIDIA package that can be installed with pip
will be made available soon.
Hugging Face pipelines provide a simple yet powerful abstraction to quickly set up inference. If you already have a pipeline from transformers, you can unlock the performance benefits of Optimum-NVIDIA by just changing one line.
- from transformers.pipelines import pipeline
+ from optimum.nvidia.pipelines import pipeline
pipe = pipeline('text-generation', 'meta-llama/Llama-2-7b-chat-hf', use_fp8=True)
pipe("Describe a real-world application of AI in sustainable energy.")
If you want control over advanced features like quantization and token seleciton strategies, we recommend using the generate()
API. Just like with pipelines
, switching from existing transformers code is super simple.
- from transformers import LlamaForCausalLM
+ from optimum.nvidia import LlamaForCausalLM
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b-chat-hf", padding_side="left")
model = LlamaForCausalLM.from_pretrained(
"meta-llama/Llama-2-7b-chat-hf",
+ use_fp8=True,
)
model_inputs = tokenizer(["How is autonomous vehicle technology transforming the future of transportation and urban planning?"], return_tensors="pt").to("cuda")
generated_ids = model.generate(
**model_inputs,
top_k=40,
top_p=0.7,
repetition_penalty=10,
)
tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
To learn more about text generation with LLMs, check out this guide!
We test Optimum-NVIDIA on 4090, L40S, and H100 Tensor Core GPUs, though it is expected to work on any GPU based on the following architectures:
Note that FP8 support is only available on GPUs based on Hopper and Ada-Lovelace architectures.
Optimum-NVIDIA works on Linux will support Windows soon.
Optimum-NVIDIA currently accelerates text-generation with LLaMAForCausalLM, and we are actively working to expand support to include more model architectures and tasks.
Check out our Contributing Guide