Instructions to use wsntxxn/effb2-trm-clotho-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wsntxxn/effb2-trm-clotho-captioning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="wsntxxn/effb2-trm-clotho-captioning", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wsntxxn/effb2-trm-clotho-captioning", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "/mnt/cloudstorfs/sjtu_home/xuenan.xu/hf_cache/hub/models--wsntxxn--effb2-trm-clotho-captioning/snapshots/a6295f4d7e0f2314bd3fc02b03512814c63fc132/", | |
| "architectures": [ | |
| "Effb2TrmCaptioningModel" | |
| ], | |
| "attn_emb_dim": 1408, | |
| "auto_map": { | |
| "AutoConfig": "hf_wrapper.Effb2TrmConfig", | |
| "AutoModel": "hf_wrapper.Effb2TrmCaptioningModel" | |
| }, | |
| "decoder_dropout": 0.2, | |
| "decoder_emb_dim": 256, | |
| "decoder_n_layers": 2, | |
| "decoder_we_tie_weights": true, | |
| "fc_emb_dim": 1408, | |
| "sample_rate": 16000, | |
| "shared_dim": 1024, | |
| "tchr_dim": 768, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.30.2", | |
| "vocab_size": 4368 | |
| } | |