Video-Text-to-Text
Transformers
Safetensors
English
gemma4
image-text-to-text
video-captioning
multimodal
gemma
parakeet
Instructions to use SulphurAI/sulphur-caption with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SulphurAI/sulphur-caption with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("SulphurAI/sulphur-caption") model = AutoModelForMultimodalLM.from_pretrained("SulphurAI/sulphur-caption", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 628 Bytes
7011765 | 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 | {
"attention_chunk_size": 12,
"attention_context_left": 13,
"attention_context_right": 0,
"attention_invalid_logits_value": -1000000000.0,
"attention_logit_cap": 50.0,
"conv_kernel_size": 5,
"dtype": "bfloat16",
"gradient_clipping": 10000000000.0,
"hidden_act": "silu",
"hidden_size": 1024,
"initializer_range": 0.02,
"model_type": "gemma4_audio",
"num_attention_heads": 8,
"num_hidden_layers": 12,
"output_proj_dims": 1536,
"residual_weight": 0.5,
"rms_norm_eps": 1e-06,
"subsampling_conv_channels": [
128,
32
],
"transformers_version": "5.12.1",
"use_clipped_linears": true
}
|