Running large language models on a single GPU for throughput-oriented scenarios.
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Updated
Apr 19, 2024 - Python
Running large language models on a single GPU for throughput-oriented scenarios.
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Train very large language models in Jax.
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This is the official PyTorch implementation of "LLM-QBench: A Benchmark Towards the Best Practice for Post-training Quantization of Large Language Models", and also an efficient LLM compression tool with various advanced compression methods, supporting multiple inference backends.
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Curated list of open source and openly accessible large language models
Small benchmark library focused on avoiding optimization/deoptimization pollution between tests by isolating them.
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[NeurIPS 2023 - ML for Audio Workshop (Oral)] Zero-shot audio captioning with audio-language model guidance and audio context keywords
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