fix ckpt_convert module to work with dreambooth v2 models

[lstein]

• Discord member @marcus.llewellyn reported that some civitai 2.1-derived checkpoints were not converting properly (probably dreambooth-generated): https://discord.com/channels/1020123559063990373/1078386197589655582/1078387806122025070

• @blessedcoolant tracked this down to a missing key that was used to derive vector length of the CLIP model used by fetching the second dimension of the tensor at "cond_stage_model.model.text_projection".

• On inspection, I found that the same second dimension can be recovered from key 'cond_stage_model.model.ln_final.bias', and use that instead. I hope this is correct; tested on multiple v1, v2 and inpainting models and they converted correctly.

• While debugging this, I found and fixed several other issues:

  • model download script was not pre-downloading the OpenCLIP text_encoder or text_tokenizer. This is fixed.
  • got rid of legacy code in ckpt_to_diffuser.py and replaced with calls into model_manager
  • more consistent status reporting in the CLI.

[blessedcoolant]

LGTM. If any exceptions pop up with edge case models, we can see if they need a hot fix or not. For now, this might work. Hard to say without trying with a bunch of varied range models. But the code reads good.