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README.md

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----
-tags:
-- image-to-text
-- image-captioning
-license: apache-2.0
-widget:
-- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
-  example_title: Savanna
-- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
-  example_title: Football Match
-- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/airport.jpg
-  example_title: Airport
----
-
-# nlpconnect/vit-gpt2-image-captioning
-
-This is an image captioning model trained by @ydshieh in [flax ](https://github.com/huggingface/transformers/tree/main/examples/flax/image-captioning) this is pytorch version of [this](https://huggingface.co/ydshieh/vit-gpt2-coco-en-ckpts).
-
-
-# The Illustrated Image Captioning using transformers
-
-![](https://ankur3107.github.io/assets/images/vision-encoder-decoder.png)
-
-* https://ankur3107.github.io/blogs/the-illustrated-image-captioning-using-transformers/
-
-
-# Sample running code
-
-```python
-
-from transformers import VisionEncoderDecoderModel, ViTImageProcessor, AutoTokenizer
-import torch
-from PIL import Image
-
-model = VisionEncoderDecoderModel.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
-feature_extractor = ViTImageProcessor.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
-tokenizer = AutoTokenizer.from_pretrained("nlpconnect/vit-gpt2-image-captioning")
-
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model.to(device)
-
-
-
-max_length = 16
-num_beams = 4
-gen_kwargs = {"max_length": max_length, "num_beams": num_beams}
-def predict_step(image_paths):
-  images = []
-  for image_path in image_paths:
-    i_image = Image.open(image_path)
-    if i_image.mode != "RGB":
-      i_image = i_image.convert(mode="RGB")
-
-    images.append(i_image)
-
-  pixel_values = feature_extractor(images=images, return_tensors="pt").pixel_values
-  pixel_values = pixel_values.to(device)
-
-  output_ids = model.generate(pixel_values, **gen_kwargs)
-
-  preds = tokenizer.batch_decode(output_ids, skip_special_tokens=True)
-  preds = [pred.strip() for pred in preds]
-  return preds
-
-
-predict_step(['doctor.e16ba4e4.jpg']) # ['a woman in a hospital bed with a woman in a hospital bed']
-
-```
-
-# Sample running code using transformers pipeline
-
-```python
-
-from transformers import pipeline
-
-image_to_text = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")
-
-image_to_text("https://ankur3107.github.io/assets/images/image-captioning-example.png")
-
-# [{'generated_text': 'a soccer game with a player jumping to catch the ball '}]
-
-
-```
-
-
-# Contact for any help
-* https://huggingface.co/ankur310794
-* https://twitter.com/ankur310794
-* http://github.com/ankur3107
-* https://www.linkedin.com/in/ankur310794

config.json

@@ -1,177 +0,0 @@
-{
-  "_name_or_path": "vit-gpt-pt",
-  "architectures": [
-    "VisionEncoderDecoderModel"
-  ],
-  "bos_token_id": 50256,
-  "decoder": {
-    "_name_or_path": "",
-    "activation_function": "gelu_new",
-    "add_cross_attention": true,
-    "architectures": [
-      "GPT2LMHeadModel"
-    ],
-    "attn_pdrop": 0.1,
-    "bad_words_ids": null,
-    "bos_token_id": 50256,
-    "chunk_size_feed_forward": 0,
-    "cross_attention_hidden_size": null,
-    "decoder_start_token_id": 50256,
-    "diversity_penalty": 0.0,
-    "do_sample": false,
-    "early_stopping": false,
-    "embd_pdrop": 0.1,
-    "encoder_no_repeat_ngram_size": 0,
-    "eos_token_id": 50256,
-    "finetuning_task": null,
-    "forced_bos_token_id": null,
-    "forced_eos_token_id": null,
-    "id2label": {
-      "0": "LABEL_0",
-      "1": "LABEL_1"
-    },
-    "initializer_range": 0.02,
-    "is_decoder": true,
-    "is_encoder_decoder": false,
-    "label2id": {
-      "LABEL_0": 0,
-      "LABEL_1": 1
-    },
-    "layer_norm_epsilon": 1e-05,
-    "length_penalty": 1.0,
-    "max_length": 20,
-    "min_length": 0,
-    "model_type": "gpt2",
-    "n_ctx": 1024,
-    "n_embd": 768,
-    "n_head": 12,
-    "n_inner": null,
-    "n_layer": 12,
-    "n_positions": 1024,
-    "no_repeat_ngram_size": 0,
-    "num_beam_groups": 1,
-    "num_beams": 1,
-    "num_return_sequences": 1,
-    "output_attentions": false,
-    "output_hidden_states": false,
-    "output_scores": false,
-    "pad_token_id": 50256,
-    "prefix": null,
-    "problem_type": null,
-    "pruned_heads": {},
-    "remove_invalid_values": false,
-    "reorder_and_upcast_attn": false,
-    "repetition_penalty": 1.0,
-    "resid_pdrop": 0.1,
-    "return_dict": true,
-    "return_dict_in_generate": false,
-    "scale_attn_by_inverse_layer_idx": false,
-    "scale_attn_weights": true,
-    "sep_token_id": null,
-    "summary_activation": null,
-    "summary_first_dropout": 0.1,
-    "summary_proj_to_labels": true,
-    "summary_type": "cls_index",
-    "summary_use_proj": true,
-    "task_specific_params": {
-      "text-generation": {
-        "do_sample": true,
-        "max_length": 50
-      }
-    },
-    "temperature": 1.0,
-    "tie_encoder_decoder": false,
-    "tie_word_embeddings": true,
-    "tokenizer_class": null,
-    "top_k": 50,
-    "top_p": 1.0,
-    "torch_dtype": null,
-    "torchscript": false,
-    "transformers_version": "4.15.0",
-    "use_bfloat16": false,
-    "use_cache": true,
-    "vocab_size": 50257
-  },
-  "decoder_start_token_id": 50256,
-  "encoder": {
-    "_name_or_path": "",
-    "add_cross_attention": false,
-    "architectures": [
-      "ViTModel"
-    ],
-    "attention_probs_dropout_prob": 0.0,
-    "bad_words_ids": null,
-    "bos_token_id": null,
-    "chunk_size_feed_forward": 0,
-    "cross_attention_hidden_size": null,
-    "decoder_start_token_id": null,
-    "diversity_penalty": 0.0,
-    "do_sample": false,
-    "early_stopping": false,
-    "encoder_no_repeat_ngram_size": 0,
-    "eos_token_id": null,
-    "finetuning_task": null,
-    "forced_bos_token_id": null,
-    "forced_eos_token_id": null,
-    "hidden_act": "gelu",
-    "hidden_dropout_prob": 0.0,
-    "hidden_size": 768,
-    "id2label": {
-      "0": "LABEL_0",
-      "1": "LABEL_1"
-    },
-    "image_size": 224,
-    "initializer_range": 0.02,
-    "intermediate_size": 3072,
-    "is_decoder": false,
-    "is_encoder_decoder": false,
-    "label2id": {
-      "LABEL_0": 0,
-      "LABEL_1": 1
-    },
-    "layer_norm_eps": 1e-12,
-    "length_penalty": 1.0,
-    "max_length": 20,
-    "min_length": 0,
-    "model_type": "vit",
-    "no_repeat_ngram_size": 0,
-    "num_attention_heads": 12,
-    "num_beam_groups": 1,
-    "num_beams": 1,
-    "num_channels": 3,
-    "num_hidden_layers": 12,
-    "num_return_sequences": 1,
-    "output_attentions": false,
-    "output_hidden_states": false,
-    "output_scores": false,
-    "pad_token_id": null,
-    "patch_size": 16,
-    "prefix": null,
-    "problem_type": null,
-    "pruned_heads": {},
-    "qkv_bias": true,
-    "remove_invalid_values": false,
-    "repetition_penalty": 1.0,
-    "return_dict": true,
-    "return_dict_in_generate": false,
-    "sep_token_id": null,
-    "task_specific_params": null,
-    "temperature": 1.0,
-    "tie_encoder_decoder": false,
-    "tie_word_embeddings": true,
-    "tokenizer_class": null,
-    "top_k": 50,
-    "top_p": 1.0,
-    "torch_dtype": null,
-    "torchscript": false,
-    "transformers_version": "4.15.0",
-    "use_bfloat16": false
-  },
-  "eos_token_id": 50256,
-  "is_encoder_decoder": true,
-  "model_type": "vision-encoder-decoder",
-  "pad_token_id": 50256,
-  "tie_word_embeddings": false,
-  "torch_dtype": "float32",
-  "transformers_version": null
-}

preprocessor_config.json

@@ -1,17 +0,0 @@
-{
-  "do_normalize": true,
-  "do_resize": true,
-  "feature_extractor_type": "ViTFeatureExtractor",
-  "image_mean": [
-    0.5,
-    0.5,
-    0.5
-  ],
-  "image_std": [
-    0.5,
-    0.5,
-    0.5
-  ],
-  "resample": 2,
-  "size": 224
-}

special_tokens_map.json

@@ -1 +0,0 @@
-{"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>", "pad_token": "<|endoftext|>"}

tokenizer_config.json

@@ -1 +0,0 @@
-{"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "add_prefix_space": false, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "./models/", "tokenizer_class": "GPT2Tokenizer"}