mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
1730a587d8
* Update TensorRT-LLM --------- Co-authored-by: tonylek <137782967+tonylek@users.noreply.github.com>
60 lines
2.7 KiB
Python
60 lines
2.7 KiB
Python
### Generation with Quantization
|
|
import logging
|
|
|
|
import torch
|
|
|
|
from tensorrt_llm import LLM, SamplingParams
|
|
from tensorrt_llm.llmapi import CalibConfig, QuantAlgo, QuantConfig
|
|
|
|
major, minor = torch.cuda.get_device_capability()
|
|
post_ada = major > 8 or (major == 8 and minor >= 9)
|
|
|
|
quant_and_calib_configs = []
|
|
|
|
# Example 1: Specify int4 AWQ quantization to QuantConfig.
|
|
# We can skip specifying CalibConfig or leave a None as the default value.
|
|
quant_and_calib_configs.append(
|
|
(QuantConfig(quant_algo=QuantAlgo.W4A16_AWQ), None))
|
|
|
|
if post_ada:
|
|
# Example 2: Specify FP8 quantization to QuantConfig.
|
|
# We can create a CalibConfig to specify the calibration dataset and other details.
|
|
# Note that the calibration dataset could be either HF dataset name or a path to local HF dataset.
|
|
quant_and_calib_configs.append(
|
|
(QuantConfig(quant_algo=QuantAlgo.FP8,
|
|
kv_cache_quant_algo=QuantAlgo.FP8),
|
|
CalibConfig(calib_dataset='cnn_dailymail',
|
|
calib_batches=256,
|
|
calib_max_seq_length=256)))
|
|
else:
|
|
logging.error(
|
|
"FP8 quantization only works on post-ada GPUs, skipped in the example.")
|
|
|
|
for quant_config, calib_config in quant_and_calib_configs:
|
|
# The built-in end-to-end quantization is triggered according to the passed quant_config.
|
|
llm = LLM(model="TinyLlama/TinyLlama-1.1B-Chat-v1.0",
|
|
quant_config=quant_config,
|
|
calib_config=calib_config)
|
|
|
|
# Sample prompts.
|
|
prompts = [
|
|
"Hello, my name is",
|
|
"The president of the United States is",
|
|
"The capital of France is",
|
|
"The future of AI is",
|
|
]
|
|
|
|
# Create a sampling params.
|
|
sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
|
|
|
|
for output in llm.generate(prompts, sampling_params):
|
|
print(
|
|
f"Prompt: {output.prompt!r}, Generated text: {output.outputs[0].text!r}"
|
|
)
|
|
|
|
# Got output like
|
|
# Prompt: 'Hello, my name is', Generated text: 'Jane Smith. I am a resident of the city. Can you tell me more about the public services provided in the area?'
|
|
# Prompt: 'The president of the United States is', Generated text: 'considered the head of state, and the vice president of the United States is considered the head of state. President and Vice President of the United States (US)'
|
|
# Prompt: 'The capital of France is', Generated text: 'located in Paris, France. The population of Paris, France, is estimated to be 2 million. France is home to many famous artists, including Picasso'
|
|
# Prompt: 'The future of AI is', Generated text: 'an open and collaborative project. The project is an ongoing effort, and we invite participation from members of the community.\n\nOur community is'
|