Instructions to use bn22/experimental-te-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bn22/experimental-te-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bn22/experimental-te-ft")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("bn22/experimental-te-ft") model = AutoModel.from_pretrained("bn22/experimental-te-ft") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "CLIPTextModel" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 49406, | |
| "dtype": "float32", | |
| "eos_token_id": 49407, | |
| "hidden_act": "gelu", | |
| "hidden_size": 384, | |
| "initializer_factor": 1.0, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 77, | |
| "model_type": "clip_text_model", | |
| "num_attention_heads": 8, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "projection_dim": 512, | |
| "transformers_version": "5.0.0", | |
| "vocab_size": 49408 | |
| } | |