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cogvlm-chat-hf

Text Generation

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nielsr HF staff commited on Mar 25

Commit

96b9145

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1 Parent(s): da2b143

Add upload_file

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Files changed (1) hide show

modeling_cogvlm.py +32 -22

modeling_cogvlm.py CHANGED Viewed

@@ -440,29 +440,29 @@ class CogVLMModel(CogVLMPreTrainedModel):
                 from huggingface_hub import HfApi
-                torch.save(images_features, "images_features.pt")
-                torch.save(inputs_embeds, "inputs_embeds.pt")
-                torch.save(token_type_ids, "token_type_ids.pt")
-                api = HfApi()
-                api.upload_file(
-                    path_or_fileobj="images_features.pt",
-                    path_in_repo="images_features.pt",
-                    repo_id="nielsr/test-cogvlm",
-                    repo_type="dataset",
-                )
-                api.upload_file(
-                    path_or_fileobj="inputs_embeds.pt",
-                    path_in_repo="inputs_embeds.pt",
-                    repo_id="nielsr/test-cogvlm",
-                    repo_type="dataset",
-                )
-                api.upload_file(
-                    path_or_fileobj="token_type_ids.pt",
-                    path_in_repo="token_type_ids.pt",
-                    repo_id="nielsr/test-cogvlm",
-                    repo_type="dataset",
-                )
                 print("First values of text embeddings:", inputs_embeds[0, :3, :3])
                 print("First values of images_features:", images_features[0, :3])
@@ -557,6 +557,16 @@ class CogVLMModel(CogVLMPreTrainedModel):
         hidden_states = inputs_embeds
         # decoder layers
         all_hidden_states = () if output_hidden_states else None
         all_self_attns = () if output_attentions else None

                 from huggingface_hub import HfApi
+                # torch.save(images_features, "images_features.pt")
+                # torch.save(inputs_embeds, "inputs_embeds.pt")
+                # torch.save(token_type_ids, "token_type_ids.pt")
+                # api = HfApi()
+                # api.upload_file(
+                #     path_or_fileobj="images_features.pt",
+                #     path_in_repo="images_features.pt",
+                #     repo_id="nielsr/test-cogvlm",
+                #     repo_type="dataset",
+                # )
+                # api.upload_file(
+                #     path_or_fileobj="inputs_embeds.pt",
+                #     path_in_repo="inputs_embeds.pt",
+                #     repo_id="nielsr/test-cogvlm",
+                #     repo_type="dataset",
+                # )
+                # api.upload_file(
+                #     path_or_fileobj="token_type_ids.pt",
+                #     path_in_repo="token_type_ids.pt",
+                #     repo_id="nielsr/test-cogvlm",
+                #     repo_type="dataset",
+                # )
                 print("First values of text embeddings:", inputs_embeds[0, :3, :3])
                 print("First values of images_features:", images_features[0, :3])
         hidden_states = inputs_embeds
+        torch.save(hidden_states, "inputs_embeds.pt")
+        api = HfApi()
+        api.upload_file(
+            path_or_fileobj="inputs_embeds.pt",
+            path_in_repo="inputs_embeds.pt",
+            repo_id="nielsr/test-cogvlm",
+            repo_type="dataset",
+        )
         # decoder layers
         all_hidden_states = () if output_hidden_states else None
         all_self_attns = () if output_attentions else None