Fix issue getting context_length and vocab_size from HF models

src/open_clip/hf_model.py

@@ -2,8 +2,8 @@
 
 Wraps HuggingFace transformers (https://github.com/huggingface/transformers) models for use as a text tower in CLIP model.
 """
-
 import re
+import warnings
 
 import torch
 import torch.nn as nn
@@ -132,7 +132,14 @@ def __init__(
             self.transformer = AutoModel.from_config(config)
         if pooler_type is None:  # get default arch pooler
             pooler_type = (arch_dict[self.config.model_type]["pooler"])
-
+
+        # FIXME downstream users of OpenCLIP models use these attr, need to verify valid across all models
+        self.vocab_size = getattr(self.config, 'vocab_size', 0)
+        self.context_length = getattr(self.config, 'max_position_embeddings', 0)
+        if not self.vocab_size or not self.context_length:
+            warnings.warn(
+                f'vocab_size ({self.vocab_size} and context_length ({self.context_length} were not properly set.')
+
         self.pooler = _POOLERS[pooler_type]()
 
         d_model = getattr(self.config, arch_dict[self.config.model_type]["config_names"]["width"])