35 lines
1.2 KiB
ReStructuredText
35 lines
1.2 KiB
ReStructuredText
.. _fp8_kv_cache:
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FP8 E5M2 KV Cache
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==================
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The int8/int4 quantization scheme requires additional scale GPU memory storage, which reduces the expected GPU memory benefits.
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The FP8 data format retains 2~3 mantissa bits and can convert float/fp16/bflaot16 and fp8 to each other.
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Here is an example of how to enable this feature:
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.. code-block:: python
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from vllm import LLM, SamplingParams
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# Sample prompts.
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prompts = [
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"Hello, my name is",
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"The president of the United States is",
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"The capital of France is",
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"The future of AI is",
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]
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# Create a sampling params object.
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sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
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# Create an LLM.
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llm = LLM(model="facebook/opt-125m", kv_cache_dtype="fp8")
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# Generate texts from the prompts. The output is a list of RequestOutput objects
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# that contain the prompt, generated text, and other information.
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outputs = llm.generate(prompts, sampling_params)
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# Print the outputs.
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for output in outputs:
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prompt = output.prompt
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generated_text = output.outputs[0].text
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print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
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