feat: add lfm2 family and latest moe model (#3208)
* feat: add lfm2 family and latest moe model * fix: use ml-cross-entropy for lfm2 examples
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@@ -6,6 +6,8 @@ LFM2 features a new hybrid Liquid architecture with multiplicative gates, short-
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This guide shows how to fine-tune both the LFM2 and LFM2-VL models with Axolotl.
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Thanks to the team at LiquidAI for giving us early access to prepare for these releases.
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## Getting Started
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1. Install Axolotl following the [installation guide](https://docs.axolotl.ai/docs/installation.html).
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@@ -31,6 +33,14 @@ This guide shows how to fine-tune both the LFM2 and LFM2-VL models with Axolotl.
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axolotl train examples/LiquidAI/lfm2-vl-lora.yaml
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```
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**LFM2-MoE**
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```bash
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pip install git+https://github.com/huggingface/transformers.git@0c9a72e4576fe4c84077f066e585129c97bfd4e6
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# LoRA SFT (1x48GB @ 16.2GiB)
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axolotl train examples/LiquidAI/lfm2-8b-a1b-lora.yaml
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```
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### TIPS
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- **Installation Error**: If you encounter `ImportError: ... undefined symbol ...` or `ModuleNotFoundError: No module named 'causal_conv1d_cuda'`, the `causal-conv1d` package may have been installed incorrectly. Try uninstalling it:
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@@ -45,14 +55,13 @@ This guide shows how to fine-tune both the LFM2 and LFM2-VL models with Axolotl.
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## Optimization Guides
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- [Multi-GPU Training](https://docs.axolotl.ai/docs/multi-gpu.html)
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- [LoRA Optimizations](https://docs.axolotl.ai/docs/lora_optims.html)
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- [Multi-Node Training](https://docs.axolotl.ai/docs/multi-node.html)
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- [Optimizations Guide](https://docs.axolotl.ai/docs/optimizations.html)
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## Related Resources
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- [LFM2 Blog](https://www.liquid.ai/blog/liquid-foundation-models-v2-our-second-series-of-generative-ai-models)
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- [LFM2-VL Blog](https://www.liquid.ai/blog/lfm2-vl-efficient-vision-language-models)
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- [LFM2-MoE Blog](https://www.liquid.ai/blog/lfm2-8b-a1b-an-efficient-on-device-mixture-of-experts)
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- [Axolotl Docs](https://docs.axolotl.ai)
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- [Axolotl GitHub](https://github.com/axolotl-ai-cloud/axolotl)
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- [Axolotl Discord](https://discord.gg/7m9sfhzaf3)
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