Instructions to use swadhindas324/convnext-Mistral-SYDNEY-without-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swadhindas324/convnext-Mistral-SYDNEY-without-captioning with Transformers:
# Load model directly from transformers import AutoTokenizer, VEDM tokenizer = AutoTokenizer.from_pretrained("swadhindas324/convnext-Mistral-SYDNEY-without-captioning") model = VEDM.from_pretrained("swadhindas324/convnext-Mistral-SYDNEY-without-captioning") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "VEDM" | |
| ], | |
| "decoder": { | |
| "_name_or_path": "swadhindas324/Mistral-SYDNEY", | |
| "add_cross_attention": true, | |
| "architectures": [ | |
| "MistralForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 480, | |
| "chunk_size_feed_forward": 0, | |
| "dtype": "float32", | |
| "eos_token_id": 481, | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": true, | |
| "is_encoder_decoder": false, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1 | |
| }, | |
| "max_position_embeddings": 45, | |
| "model_type": "mistral", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "num_key_value_heads": 4, | |
| "output_attentions": false, | |
| "output_hidden_states": false, | |
| "pad_token_id": 483, | |
| "problem_type": null, | |
| "return_dict": true, | |
| "rms_norm_eps": 1e-06, | |
| "rope_parameters": { | |
| "rope_theta": 10000.0, | |
| "rope_type": "default" | |
| }, | |
| "sliding_window": 4096, | |
| "tie_word_embeddings": false, | |
| "type_vocab_size": 1, | |
| "use_cache": false, | |
| "vocab_size": 484 | |
| }, | |
| "decoder_start_token_id": 480, | |
| "dtype": "float32", | |
| "encoder": { | |
| "_name_or_path": "swadhindas324/convnext-vit", | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "ConvNext_Backbone" | |
| ], | |
| "chunk_size_feed_forward": 0, | |
| "dropout_rate": 0.1, | |
| "dtype": "float32", | |
| "embed_dim": 1536, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1" | |
| }, | |
| "is_decoder": false, | |
| "is_encoder_decoder": false, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1 | |
| }, | |
| "mlp_dim": 3072, | |
| "model_type": "convnext_vit", | |
| "num_heads": 8, | |
| "num_layers": 12, | |
| "output_attentions": false, | |
| "output_hidden_states": false, | |
| "patch_size": 49, | |
| "problem_type": null, | |
| "return_dict": true | |
| }, | |
| "is_encoder_decoder": true, | |
| "model_type": "vision-encoder-decoder", | |
| "pad_token_id": 483, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "5.12.1", | |
| "use_cache": false, | |
| "vocab_size": 484 | |
| } | |