chore: update doc links (#2509)

* chore: update doc links

* fix: address pr feedback
This commit is contained in:
NanoCode012
2025-04-11 20:53:18 +07:00
committed by GitHub
parent 756a0559c1
commit 51267ded04
4 changed files with 17 additions and 19 deletions

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@@ -63,7 +63,7 @@ axolotl fetch examples
axolotl fetch deepspeed_configs # OPTIONAL
```
Other installation approaches are described [here](https://axolotl-ai-cloud.github.io/axolotl/docs/installation.html).
Other installation approaches are described [here](https://docs.axolotl.ai/docs/installation.html).
### Your First Fine-tune
@@ -78,7 +78,7 @@ axolotl fetch examples --dest path/to/folder
axolotl train examples/llama-3/lora-1b.yml
```
That's it! Check out our [Getting Started Guide](https://axolotl-ai-cloud.github.io/axolotl/docs/getting-started.html) for a more detailed walkthrough.
That's it! Check out our [Getting Started Guide](https://docs.axolotl.ai/docs/getting-started.html) for a more detailed walkthrough.
## ✨ Key Features
@@ -91,20 +91,20 @@ That's it! Check out our [Getting Started Guide](https://axolotl-ai-cloud.github
## 📚 Documentation
- [Installation Options](https://axolotl-ai-cloud.github.io/axolotl/docs/installation.html) - Detailed setup instructions for different environments
- [Configuration Guide](https://axolotl-ai-cloud.github.io/axolotl/docs/config.html) - Full configuration options and examples
- [Dataset Guide](https://axolotl-ai-cloud.github.io/axolotl/docs/dataset-formats/) - Supported formats and how to use them
- [Multi-GPU Training](https://axolotl-ai-cloud.github.io/axolotl/docs/multi-gpu.html)
- [Multi-Node Training](https://axolotl-ai-cloud.github.io/axolotl/docs/multi-node.html)
- [Multipacking](https://axolotl-ai-cloud.github.io/axolotl/docs/multipack.html)
- [API Reference](https://axolotl-ai-cloud.github.io/axolotl/docs/api/) - Auto-generated code documentation
- [FAQ](https://axolotl-ai-cloud.github.io/axolotl/docs/faq.html) - Frequently asked questions
- [Installation Options](https://docs.axolotl.ai/docs/installation.html) - Detailed setup instructions for different environments
- [Configuration Guide](https://docs.axolotl.ai/docs/config.html) - Full configuration options and examples
- [Dataset Guide](https://docs.axolotl.ai/docs/dataset-formats/) - Supported formats and how to use them
- [Multi-GPU Training](https://docs.axolotl.ai/docs/multi-gpu.html)
- [Multi-Node Training](https://docs.axolotl.ai/docs/multi-node.html)
- [Multipacking](https://docs.axolotl.ai/docs/multipack.html)
- [API Reference](https://docs.axolotl.ai/docs/api/) - Auto-generated code documentation
- [FAQ](https://docs.axolotl.ai/docs/faq.html) - Frequently asked questions
## 🤝 Getting Help
- Join our [Discord community](https://discord.gg/HhrNrHJPRb) for support
- Check out our [Examples](https://github.com/axolotl-ai-cloud/axolotl/tree/main/examples/) directory
- Read our [Debugging Guide](https://axolotl-ai-cloud.github.io/axolotl/docs/debugging.html)
- Read our [Debugging Guide](https://docs.axolotl.ai/docs/debugging.html)
- Need dedicated support? Please contact [wing@axolotl.ai](mailto:wing@axolotl.ai) for options
## 🌟 Contributing

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@@ -90,7 +90,7 @@ lora_on_cpu: true
# List[str]. Add plugins to extend the pipeline.
# See `src/axolotl/integrations` for the available plugins or doc below for more details.
# https://axolotl-ai-cloud.github.io/axolotl/docs/custom_integrations.html
# https://docs.axolotl.ai/docs/custom_integrations.html
plugins:
# - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
@@ -394,7 +394,7 @@ lora_fan_in_fan_out: false
# Apply custom LoRA autograd functions and activation function Triton kernels for
# speed and memory savings
# See: https://axolotl-ai-cloud.github.io/axolotl/docs/lora_optims.html
# See: https://docs.axolotl.ai/docs/lora_optims.html
lora_mlp_kernel: true
lora_qkv_kernel: true
lora_o_kernel: true
@@ -688,7 +688,7 @@ ddp_broadcast_buffers:
# Use in long context training to prevent OOM when sequences cannot fit into a single GPU's VRAM.
# E.g., if 4 GPUs are available, set this value to 2 to split each sequence into two equal-sized
# subsequences, or set to 4 to split into four equal-sized subsequences.
# See https://axolotl-ai-cloud.github.io/axolotl/docs/sequence_parallelism.html for more details.
# See https://docs.axolotl.ai/docs/sequence_parallelism.html for more details.
sequence_parallel_degree:
# Optional; strides across the key dimension. Larger values use more memory but should make training faster.
# Must evenly divide the number of KV heads in your model.

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@@ -457,10 +457,7 @@ datasets:
type: alpaca
```
Axolotl supports many kinds of instruction dataset. All of them can be found here (https://axolotl-ai-cloud.github.io/axolotl/docs/dataset-formats/inst_tune.html) with their respective type and sample row format.
Reference: [Instruction Dataset Documentation](inst_tune.qmd).
Axolotl supports many kinds of instruction dataset. All of them can be found in the [Instruction Dataset Documentation](inst_tune.qmd) with their respective type and sample row format.
#### Custom Instruct Prompt Format

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@@ -14,7 +14,8 @@ requires-python = ">=3.10"
axolotl = "axolotl.cli.main:main"
[project.urls]
Homepage = "https://axolotl-ai-cloud.github.io/axolotl/"
Homepage = "https://axolotl.ai/"
Documentation = "https://docs.axolotl.ai/"
Repository = "https://github.com/axolotl-ai-cloud/axolotl.git"
[tool.setuptools_scm]