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Patrick Devine 2024-08-26 18:09:21 -07:00
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@ -80,9 +80,7 @@ This includes importing foundation models as well as any fine tuned models which
If you have a GGUF based model or adapter it is possible to import it into Ollama. You can obtain a GGUF model or adapter by: If you have a GGUF based model or adapter it is possible to import it into Ollama. You can obtain a GGUF model or adapter by:
* converting a Safetensors model with the `convert_hf_to_gguf.py` from Llama.cpp; * converting a Safetensors model with the `convert_hf_to_gguf.py` from Llama.cpp;
* converting a Safetensors adapter with the `convert_lora_to_gguf.py` from Llama.cpp; or * converting a Safetensors adapter with the `convert_lora_to_gguf.py` from Llama.cpp; or
* downloading a model or adapter from a place such as HuggingFace * downloading a model or adapter from a place such as HuggingFace
To import a GGUF model, create a `Modelfile` containg: To import a GGUF model, create a `Modelfile` containg:
@ -101,12 +99,9 @@ ADAPTER /path/to/file.gguf
When importing a GGUF adapter, it's important to use the same base model as the base model that the adapter was created with. You can use: When importing a GGUF adapter, it's important to use the same base model as the base model that the adapter was created with. You can use:
* a model from Ollama * a model from Ollama
* a GGUF file * a GGUF file
* a Safetensors based model * a Safetensors based model
## Quantizing a Model ## Quantizing a Model
Quantizing a model allows you to run models faster and with less memory consumption but at reduced accuracy. This allows you to run a model on more modest hardware. Quantizing a model allows you to run models faster and with less memory consumption but at reduced accuracy. This allows you to run a model on more modest hardware.