6de207de88
## Summary
Fix typos and improve grammar consistency across 50 documentation files.
### Changes include:
- Spelling corrections (e.g., "Facotory" → "Factory", "certainty" →
"determinism")
- Grammar improvements (e.g., "multi-thread" → "multi-threaded",
"re-routed" → "re-run")
- Punctuation fixes (semicolon consistency in filter parameters)
- Code style fixes (correct flag name `--num-prompts` instead of
`--num-prompt`)
- Capitalization consistency (e.g., "python" → "Python", "ascend" →
"Ascend")
- vLLM version: v0.15.0
- vLLM main:
9562912cea
---------
Signed-off-by: SlightwindSec <slightwindsec@gmail.com>
1.1 KiB
LLaMA-Factory
Introduction
LLaMA-Factory is an easy-to-use and efficient platform for training and fine-tuning large language models. With LLaMA-Factory, you can fine-tune hundreds of pre-trained models locally without writing any code.
LLaMA-Factory users need to evaluate and inference the model after fine-tuning.
Business challenge
LLaMA-Factory uses Transformers to perform inference on Ascend NPUs, but the speed is slow.
Benefits with vLLM Ascend
With the joint efforts of LLaMA-Factory and vLLM Ascend (LLaMA-Factory#7739), LLaMA-Factory has achieved significant performance gains during model inference. Benchmark results show that its inference speed is now up to 2× faster compared to the Transformers implementation.
Learn more
See more details about LLaMA-Factory and how it uses vLLM Ascend for inference on Ascend NPUs in LLaMA-Factory Ascend NPU Inference.