From ee89b24879fb65ca9e1c6d043e641c23de6bbfce Mon Sep 17 00:00:00 2001 From: latent-9 <296084221+latent-9@users.noreply.github.com> Date: Sat, 1 Aug 2026 05:51:47 +1200 Subject: [PATCH] docs: fix example config paths in English installation guide MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The English quick-start referenced examples/v1/sft_qwen3_tiny.py and examples/v1/sft_intern_s1_tiny_config.py, which 404 — the configs live under examples/v1/config/. The Chinese installation guide already uses the correct examples/v1/config/ paths; this brings the English doc in line so the documented torchrun commands run. --- docs/en/get_started/installation.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/en/get_started/installation.md b/docs/en/get_started/installation.md index 2e8f569d1f..20feefac98 100644 --- a/docs/en/get_started/installation.md +++ b/docs/en/get_started/installation.md @@ -68,7 +68,7 @@ Having problems running? Check out the [FAQ](faq) :caption: dense model fine-tuning example :linenos: -torchrun xtuner/v1/train/cli/sft.py --model-cfg examples/v1/sft_qwen3_tiny.py --chat_template qwen3 --dataset tests/resource/openai_sft.jsonl +torchrun xtuner/v1/train/cli/sft.py --model-cfg examples/v1/config/sft_qwen3_tiny.py --chat_template qwen3 --dataset tests/resource/openai_sft.jsonl ``` After successful execution, the log is as follows @@ -91,7 +91,7 @@ After successful execution, the log is as follows ``` ```` -The above log shows that only 8G of memory is needed to run. If you want to reduce memory usage further, you can consider modifying the `num_hidden_layers` and `hidden_size` parameters in `examples/v1/sft_qwen3_tiny.py`. +The above log shows that only 8G of memory is needed to run. If you want to reduce memory usage further, you can consider modifying the `num_hidden_layers` and `hidden_size` parameters in `examples/v1/config/sft_qwen3_tiny.py`. ### MLLM Multimodal Large Model Fine-tuning @@ -103,7 +103,7 @@ Take Intern-S1 scientific multimodal as an example :caption: Intern-S1 tiny model fine-tuning example :linenos: -torchrun xtuner/v1/train/cli/sft.py --config examples/v1/sft_intern_s1_tiny_config.py +torchrun xtuner/v1/train/cli/sft.py --config examples/v1/config/sft_intern_s1_tiny_config.py ``` After successful execution, the log is as follows @@ -267,7 +267,7 @@ WARNING: input_ids length 4171 exceeds model_max_length 4096. truncated! ``` ```` -The above log shows that only 10G of memory is needed to run. If you want to reduce memory usage further, you can consider modifying the `llm_cfg` dictionary related parameters in `examples/v1/sft_intern_s1_tiny_config.py`. +The above log shows that only 10G of memory is needed to run. If you want to reduce memory usage further, you can consider modifying the `llm_cfg` dictionary related parameters in `examples/v1/config/sft_intern_s1_tiny_config.py`. (faq)= ## FAQ