feat(ml): export clip models to ONNX and host models on Hugging Face (#4700)

* export clip models

* export to hf

refactored export code

* export mclip, general refactoring

cleanup

* updated conda deps

* do transforms with pillow and numpy, add tokenization config to export, general refactoring

* moved conda dockerfile, re-added poetry

* minor fixes

* updated link

* updated tests

* removed `requirements.txt` from workflow

* fixed mimalloc path

* removed torchvision

* cleaner np typing

* review suggestions

* update default model name

* update test

machine-learning/app/models/cache.py

@@ -4,6 +4,8 @@ from aiocache.backends.memory import SimpleMemoryCache
 from aiocache.lock import OptimisticLock
 from aiocache.plugins import BasePlugin, TimingPlugin
 
+from app.models import from_model_type
+
 from ..schemas import ModelType
 from .base import InferenceModel
 
@@ -50,7 +52,7 @@ class ModelCache:
         async with OptimisticLock(self.cache, key) as lock:
             model = await self.cache.get(key)
             if model is None:
-                model = InferenceModel.from_model_type(model_type, model_name, **model_kwargs)
+                model = from_model_type(model_type, model_name, **model_kwargs)
                 await lock.cas(model, ttl=self.ttl)
         return model