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oobabooga 2023-11-19 13:34:21 -03:00
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Home.md

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| Loader | Loading 1 LoRA | Loading 2 or more LoRAs | Training LoRAs | Multimodal extension | Perplexity evaluation | | Loader | Loading 1 LoRA | Loading 2 or more LoRAs | Training LoRAs | Multimodal extension | Perplexity evaluation |
|----------------|----------------|-------------------------|----------------|----------------------|-----------------------| |----------------|----------------|-------------------------|----------------|----------------------|-----------------------|
| Transformers | ✅ | ✅ | ✅* | ✅ | ✅ | | Transformers | ✅ | ✅*** | ✅* | ✅ | ✅ |
| ExLlama_HF | ✅ | ❌ | ❌ | ❌ | ✅ | | ExLlama_HF | ✅ | ❌ | ❌ | ❌ | ✅ |
| ExLlamav2_HF | ✅ | ✅ | ❌ | ❌ | ✅ | | ExLlamav2_HF | ✅ | ✅ | ❌ | ❌ | ✅ |
| ExLlama | ✅ | ❌ | ❌ | ❌ | use ExLlama_HF | | ExLlama | ✅ | ❌ | ❌ | ❌ | use ExLlama_HF |
| ExLlamav2 | ✅ | ✅ | ❌ | ❌ | use ExLlamav2_HF | | ExLlamav2 | ✅ | ✅ | ❌ | ❌ | use ExLlamav2_HF |
| AutoGPTQ | ✅ | ❌ | ❌ | ✅ | ✅ | | AutoGPTQ | ✅ | ❌ | ❌ | ✅ | ✅ |
| GPTQ-for-LLaMa | ✅** | ✅ | ✅ | ✅ | ✅ | | GPTQ-for-LLaMa | ✅** | ✅*** | ✅ | ✅ | ✅ |
| llama.cpp | ❌ | ❌ | ❌ | ❌ | use llamacpp_HF | | llama.cpp | ❌ | ❌ | ❌ | ❌ | use llamacpp_HF |
| llamacpp_HF | ❌ | ❌ | ❌ | ❌ | ✅ | | llamacpp_HF | ❌ | ❌ | ❌ | ❌ | ✅ |
| ctransformers | ❌ | ❌ | ❌ | ❌ | ❌ | | ctransformers | ❌ | ❌ | ❌ | ❌ | ❌ |
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\* Training LoRAs with GPTQ models also works with the Transformers loader. Make sure to check "auto-devices" and "disable_exllama" before loading the model. \* Training LoRAs with GPTQ models also works with the Transformers loader. Make sure to check "auto-devices" and "disable_exllama" before loading the model.
\*\* Requires the monkey-patch. The instructions can be found [here](https://github.com/oobabooga/text-generation-webui/wiki/08-%E2%80%90-Additional-Tips#using-loras-with-gptq-for-llama). \*\* Requires the monkey-patch. The instructions can be found [here](https://github.com/oobabooga/text-generation-webui/wiki/08-%E2%80%90-Additional-Tips#using-loras-with-gptq-for-llama).
\*\*\* Multi-LoRA in PEFT is tricky and the current implementation does not work reliably in all cases.