Instructions to use peft-internal-testing/tiny-clip-text-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peft-internal-testing/tiny-clip-text-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, CLIPTextModelWithProjection tokenizer = AutoTokenizer.from_pretrained("peft-internal-testing/tiny-clip-text-2") model = CLIPTextModelWithProjection.from_pretrained("peft-internal-testing/tiny-clip-text-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from peft-internal-testing/tiny-clip-text-2: direct link, hf CLI and curl.
- Browser
- Download file 548 Bytes
-
https://huggingface.co/peft-internal-testing/tiny-clip-text-2/resolve/main/config.json
- Command line
-
hf download hf://peft-internal-testing/tiny-clip-text-2/config.json
-
curl -L -o config.json https://huggingface.co/peft-internal-testing/tiny-clip-text-2/resolve/main/config.json
548 Bytes
| { | |
| "architectures": [ | |
| "CLIPTextModelWithProjection" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 0, | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_size": 32, | |
| "initializer_factor": 1.0, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 37, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 77, | |
| "model_type": "clip_text_model", | |
| "num_attention_heads": 4, | |
| "num_hidden_layers": 5, | |
| "pad_token_id": 1, | |
| "projection_dim": 32, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.34.0.dev0", | |
| "vocab_size": 1000 | |
| } | |