[BOUNTY - $200] Support MLX community models in tinygrad inference engine

[AlexCheema]

• This is a follow up to #148
• In general model weights on huggingface are a bit of a mess because of different implementations in ML libraries. For example, tinygrad implementation of models name things slightly differently to MLX implementation, which names things slightly different to torch implementation
• This means we need to have some code that "converts" these names / structure to the tinygrad one
• Right now there's some code that already does this to convert from the huggingface torch implementation to tinygrad: https://github.com/exo-explore/exo/blob/41f0a22e76ae57f5993fd57695fb4b3200e29c50/exo/inference/tinygrad/models/llama.py#L220-L249. We just need something that can also deal with MLX community models e.g. https://huggingface.co/mlx-community/Meta-Llama-3.1-8B-Instruct-4bit
• Note, you can look at how MLX does this here (you might be able to share a lot of code from there): https://github.com/ml-explore/mlx-examples/blob/bd29aec299c8fa59c161a9c1207bfc59db31d845/llms/mlx_lm/utils.py#L700

[radenmuaz]

Does this bounty also requires porting mlx modelling code to tinygrad? Since according to mlx-examples library, different models on mlx-community requires different modelling code. exo currently only has llama. llama tinygrad modelling code is incompatible (different) with weights from qwen, etc.

https://github.com/ml-explore/mlx-examples/blob/bd6d910ca3744d75bf704e6e7039f97f71014bd5/llms/mlx_lm/utils.py#L81

though if models are ported from mlx to tinygrad, we don't need converter anymore.