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skills/mlops/training/axolotl/SKILL.md

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+---
+name: axolotl
+description: Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support
+version: 1.0.0
+author: Orchestra Research
+license: MIT
+dependencies: [axolotl, torch, transformers, datasets, peft, accelerate, deepspeed]
+metadata:
+  hermes:
+    tags: [Fine-Tuning, Axolotl, LLM, LoRA, QLoRA, DPO, KTO, ORPO, GRPO, YAML, HuggingFace, DeepSpeed, Multimodal]
+
+---
+
+# Axolotl Skill
+
+Comprehensive assistance with axolotl development, generated from official documentation.
+
+## When to Use This Skill
+
+This skill should be triggered when:
+- Working with axolotl
+- Asking about axolotl features or APIs
+- Implementing axolotl solutions
+- Debugging axolotl code
+- Learning axolotl best practices
+
+## Quick Reference
+
+### Common Patterns
+
+**Pattern 1:** To validate that acceptable data transfer speeds exist for your training job, running NCCL Tests can help pinpoint bottlenecks, for example:
+
+```
+./build/all_reduce_perf -b 8 -e 128M -f 2 -g 3
+```
+
+**Pattern 2:** Configure your model to use FSDP in the Axolotl yaml. For example:
+
+```
+fsdp_version: 2
+fsdp_config:
+  offload_params: true
+  state_dict_type: FULL_STATE_DICT
+  auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  transformer_layer_cls_to_wrap: LlamaDecoderLayer
+  reshard_after_forward: true
+```
+
+**Pattern 3:** The context_parallel_size should be a divisor of the total number of GPUs. For example:
+
+```
+context_parallel_size
+```
+
+**Pattern 4:** For example: - With 8 GPUs and no sequence parallelism: 8 different batches processed per step - With 8 GPUs and context_parallel_size=4: Only 2 different batches processed per step (each split across 4 GPUs) - If your per-GPU micro_batch_size is 2, the global batch size decreases from 16 to 4
+
+```
+context_parallel_size=4
+```
+
+**Pattern 5:** Setting save_compressed: true in your configuration enables saving models in a compressed format, which: - Reduces disk space usage by approximately 40% - Maintains compatibility with vLLM for accelerated inference - Maintains compatibility with llmcompressor for further optimization (example: quantization)
+
+```
+save_compressed: true
+```
+
+**Pattern 6:** Note It is not necessary to place your integration in the integrations folder. It can be in any location, so long as it’s installed in a package in your python env. See this repo for an example: https://github.com/axolotl-ai-cloud/diff-transformer
+
+```
+integrations
+```
+
+**Pattern 7:** Handle both single-example and batched data. - single example: sample[‘input_ids’] is a list[int] - batched data: sample[‘input_ids’] is a list[list[int]]
+
+```
+utils.trainer.drop_long_seq(sample, sequence_len=2048, min_sequence_len=2)
+```
+
+### Example Code Patterns
+
+**Example 1** (python):
+```python
+cli.cloud.modal_.ModalCloud(config, app=None)
+```
+
+**Example 2** (python):
+```python
+cli.cloud.modal_.run_cmd(cmd, run_folder, volumes=None)
+```
+
+**Example 3** (python):
+```python
+core.trainers.base.AxolotlTrainer(
+    *_args,
+    bench_data_collator=None,
+    eval_data_collator=None,
+    dataset_tags=None,
+    **kwargs,
+)
+```
+
+**Example 4** (python):
+```python
+core.trainers.base.AxolotlTrainer.log(logs, start_time=None)
+```
+
+**Example 5** (python):
+```python
+prompt_strategies.input_output.RawInputOutputPrompter()
+```
+
+## Reference Files
+
+This skill includes comprehensive documentation in `references/`:
+
+- **api.md** - Api documentation
+- **dataset-formats.md** - Dataset-Formats documentation
+- **other.md** - Other documentation
+
+Use `view` to read specific reference files when detailed information is needed.
+
+## Working with This Skill
+
+### For Beginners
+Start with the getting_started or tutorials reference files for foundational concepts.
+
+### For Specific Features
+Use the appropriate category reference file (api, guides, etc.) for detailed information.
+
+### For Code Examples
+The quick reference section above contains common patterns extracted from the official docs.
+
+## Resources
+
+### references/
+Organized documentation extracted from official sources. These files contain:
+- Detailed explanations
+- Code examples with language annotations
+- Links to original documentation
+- Table of contents for quick navigation
+
+### scripts/
+Add helper scripts here for common automation tasks.
+
+### assets/
+Add templates, boilerplate, or example projects here.
+
+## Notes
+
+- This skill was automatically generated from official documentation
+- Reference files preserve the structure and examples from source docs
+- Code examples include language detection for better syntax highlighting
+- Quick reference patterns are extracted from common usage examples in the docs
+
+## Updating
+
+To refresh this skill with updated documentation:
+1. Re-run the scraper with the same configuration
+2. The skill will be rebuilt with the latest information
+
+

skills/mlops/training/axolotl/references/index.md

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+# Axolotl Documentation Index
+
+## Categories
+
+### Api
+**File:** `api.md`
+**Pages:** 150
+
+### Dataset-Formats
+**File:** `dataset-formats.md`
+**Pages:** 9
+
+### Other
+**File:** `other.md`
+**Pages:** 26