Gemma integration

[Isaina]

Hi

can you also implement gemma model to compare with llama

best regards

[AbeEstrada]

@Isaina open query_vdb.py and replace:

- 36 model, tokenizer = load("mlx-community/NeuralBeagle14-7B-4bit-mlx")
+ 36 model, tokenizer = load("mlx-community/quantized-gemma-2b-it")

[Isaina]

Can YOU also support mlx on Intel macos platform

[AbeEstrada]

@Isaina No, mlx was created for Apple silicon. If you want to use Intel try llama.cpp

[Isaina]

Ok thanks for gemma information On 05.04.2024. at 18:50, Abe Estrada wrote: From: "Abe Estrada" ***@***.***>Date: 5 April 2024To: "vegaluisjose/mlx-rag" ***@***.***>Cc: "Mention" ***@***.***>,"Isaina" ***@***.***>Subject: Re: [vegaluisjose/mlx-rag] Gemma integration (Issue #4) @Isaina no, mlx was created for Apple silicon —Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you were mentioned.Message ID: ***@***.***>