Support revision in Flax text-to-image training (#2567)

Support revision in Flax text-to-image training.

examples/text_to_image/train_text_to_image_flax.py

@@ -48,6 +48,13 @@ def parse_args():
         required=True,
         help="Path to pretrained model or model identifier from huggingface.co/models.",
     )
+    parser.add_argument(
+        "--revision",
+        type=str,
+        default=None,
+        required=False,
+        help="Revision of pretrained model identifier from huggingface.co/models.",
+    )
     parser.add_argument(
         "--dataset_name",
         type=str,
@@ -386,15 +393,17 @@ def main():
         weight_dtype = jnp.bfloat16
 
     # Load models and create wrapper for stable diffusion
-    tokenizer = CLIPTokenizer.from_pretrained(args.pretrained_model_name_or_path, subfolder="tokenizer")
+    tokenizer = CLIPTokenizer.from_pretrained(
+        args.pretrained_model_name_or_path, revision=args.revision, subfolder="tokenizer"
+    )
     text_encoder = FlaxCLIPTextModel.from_pretrained(
-        args.pretrained_model_name_or_path, subfolder="text_encoder", dtype=weight_dtype
+        args.pretrained_model_name_or_path, revision=args.revision, subfolder="text_encoder", dtype=weight_dtype
     )
     vae, vae_params = FlaxAutoencoderKL.from_pretrained(
-        args.pretrained_model_name_or_path, subfolder="vae", dtype=weight_dtype
+        args.pretrained_model_name_or_path, revision=args.revision, subfolder="vae", dtype=weight_dtype
     )
     unet, unet_params = FlaxUNet2DConditionModel.from_pretrained(
-        args.pretrained_model_name_or_path, subfolder="unet", dtype=weight_dtype
+        args.pretrained_model_name_or_path, revision=args.revision, subfolder="unet", dtype=weight_dtype
     )
 
     # Optimization