Instructions to use deepakachu/rsicd_image_captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepakachu/rsicd_image_captioning with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="deepakachu/rsicd_image_captioning")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("deepakachu/rsicd_image_captioning") model = AutoModelForImageTextToText.from_pretrained("deepakachu/rsicd_image_captioning") - Notebooks
- Google Colab
- Kaggle
File size: 859 Bytes
50dfa12 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | {
"_name_or_path": "microsoft/git-base",
"architectures": [
"GitForCausalLM"
],
"attention_probs_dropout_prob": 0.1,
"bos_token_id": 101,
"classifier_dropout": null,
"eos_token_id": 102,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 1024,
"model_type": "git",
"num_attention_heads": 12,
"num_hidden_layers": 6,
"num_image_with_embedding": null,
"pad_token_id": 0,
"position_embedding_type": "absolute",
"tie_word_embeddings": false,
"torch_dtype": "float32",
"transformers_version": "4.37.0",
"use_cache": true,
"vision_config": {
"dropout": 0.0,
"initializer_factor": 1.0,
"model_type": "git_vision_model",
"projection_dim": 512
},
"vocab_size": 30522
}
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