96ae8bdd1d
* Add troubleshooting note for GLM4 GGUF MTP mismatch * Fix JSON syntax for num_nextn_predict_layers example * fix: concise --------- Co-authored-by: NanoCode012 <nano@axolotl.ai>
81 lines
2.7 KiB
Markdown
81 lines
2.7 KiB
Markdown
# Finetune Z.ai's GLM-4.5-Air with Axolotl
|
|
|
|
[GLM-4.5-Air](https://huggingface.co/zai-org/GLM-4.5-Air) is a MoE model by Z.ai.
|
|
|
|
This guide shows how to fine-tune it with Axolotl.
|
|
|
|
## Getting started
|
|
|
|
1. Install Axolotl following the [installation guide](https://docs.axolotl.ai/docs/installation.html).
|
|
|
|
2. Install [Cut Cross Entropy](https://docs.axolotl.ai/docs/custom_integrations.html#cut-cross-entropy) to reduce training VRAM usage.
|
|
|
|
3. Run the finetuning example:
|
|
|
|
```bash
|
|
# QLoRA (1x80GB @ ~63.4GiB/GPU)
|
|
axolotl train examples/glm45/glm-45-air-qlora.yaml
|
|
```
|
|
|
|
### Dataset
|
|
|
|
In addition to the standard OpenAI Messages format, GLM-4.5 supports an extra parameter for thinking in the assistant section.
|
|
|
|
```json
|
|
{
|
|
"role": "assistant",
|
|
"reasoning_content": "...", // or have </think>...</think> in `content`
|
|
"content": "..."
|
|
}
|
|
```
|
|
|
|
Make sure you set the below extra attributes if needed:
|
|
|
|
```yaml
|
|
datasets:
|
|
- path: ...
|
|
type: chat_template
|
|
message_property_mappings:
|
|
role: role
|
|
content: content
|
|
|
|
# tool_calls: tool_calls # uncomment if using tools
|
|
# reasoning_content: reasoning_content # uncomment if have reasoning
|
|
|
|
# Uncomment if training on tool role (you would rarely if ever need this)
|
|
# eot_tokens:
|
|
# - <|observation|>
|
|
```
|
|
|
|
### Tips
|
|
|
|
- The role name for tools in this template is `tool`.
|
|
- You will see this Axolotl WARNING — this is expected as the template does not use EOS:
|
|
```
|
|
EOS token '<|endoftext|>' not found in chat_template. Please check if your template/EOS token is correct.
|
|
```
|
|
- You can run a full finetuning by removing `adapter: qlora`, `load_in_4bit: true`, and `quantize_moe_experts: true` from the config.
|
|
- **LoRA kernels**: Incompatible with this model. Must be explicitly disabled (`lora_*_kernel: false`).
|
|
- Read more on how to load your own dataset at [docs](https://docs.axolotl.ai/docs/dataset_loading.html).
|
|
|
|
### GGUF / llama.cpp loading error (missing tensors)
|
|
|
|
If you see `missing tensor 'blk.X.attn_norm.weight'` when loading a GLM-4 / GLM4-MoE model in llama.cpp, this is likely
|
|
caused by `num_nextn_predict_layers` being set to `1` in `config.json` while the MTP weights were not exported (possible
|
|
after PEFT/QLoRA training).
|
|
|
|
**Fix:** Set `"num_nextn_predict_layers": 0` in your `config.json` before converting to GGUF.
|
|
|
|
## Optimization Guides
|
|
|
|
Please check the [Optimizations doc](https://docs.axolotl.ai/docs/optimizations.html).
|
|
|
|
## Related Resources
|
|
|
|
- [GLM-4.5-Air on HuggingFace](https://huggingface.co/zai-org/GLM-4.5-Air)
|
|
- [GLM-4.5 Blog](https://z.ai/blog/glm-4.5)
|
|
- [Axolotl Docs](https://docs.axolotl.ai)
|
|
- [Axolotl Website](https://axolotl.ai)
|
|
- [Axolotl GitHub](https://github.com/axolotl-ai-cloud/axolotl)
|
|
- [Axolotl Discord](https://discord.gg/7m9sfhzaf3)
|