Instructions to use fusing/latent-diffusion-text2im-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/latent-diffusion-text2im-large with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/latent-diffusion-text2im-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 647 Bytes
030d953 | 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 | {
"_name_or_path": "../fusing-models/bert/",
"activation_dropout": 0.0,
"activation_function": "gelu",
"architectures": [
"LDMBertModel"
],
"attention_dropout": 0.0,
"classifier_dropout": 0.0,
"d_model": 1280,
"dropout": 0.1,
"encoder_attention_heads": 8,
"encoder_ffn_dim": 5120,
"encoder_layerdrop": 0.0,
"encoder_layers": 32,
"head_dim": 64,
"init_std": 0.02,
"max_position_embeddings": 77,
"model_type": "ldmbert",
"num_hidden_layers": 32,
"pad_token_id": 0,
"scale_embedding": false,
"torch_dtype": "float32",
"transformers_version": "4.20.0.dev0",
"use_cache": true,
"vocab_size": 30522
}
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