Text-to-Image
Transformers
PyTorch
Chinese
altclip
zero-shot-image-classification
stable-diffusion
stable-diffusion-diffusers
Chinese
multilingual
English(En)
Chinese(Zh)
Spanish(Es)
French(Fr)
Russian(Ru)
Japanese(Ja)
Korean(Ko)
Arabic(Ar)
Italian(It)
Instructions to use BAAI/AltCLIP-m9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/AltCLIP-m9 with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("BAAI/AltCLIP-m9") model = AutoModelForZeroShotImageClassification.from_pretrained("BAAI/AltCLIP-m9") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "mask_token": { | |
| "__type": "AddedToken", | |
| "content": "<mask>", | |
| "lstrip": true, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "model_max_length": 512, | |
| "name_or_path": "xlm-roberta-large", | |
| "pad_token": "<pad>", | |
| "processor_class": "CHCLIPProcess", | |
| "sep_token": "</s>", | |
| "special_tokens_map_file": null, | |
| "tokenizer_class": "XLMRobertaTokenizer", | |
| "unk_token": "<unk>" | |
| } | |