Instructions to use Xenova/text-embedding-ada-002 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Xenova/text-embedding-ada-002 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Xenova/text-embedding-ada-002", device_map="auto") - Transformers.js
How to use Xenova/text-embedding-ada-002 with Transformers.js:
// ⚠️ Unknown pipeline tag
- Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Xenova/text-embedding-ada-002: direct link, hf CLI and curl.
- Browser
- Download file 234 Bytes
-
https://huggingface.co/Xenova/text-embedding-ada-002/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Xenova/text-embedding-ada-002/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Xenova/text-embedding-ada-002/resolve/main/tokenizer_config.json
234 Bytes
| { | |
| "add_prefix_space": false, | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|endoftext|>", | |
| "model_max_length": 8192, | |
| "tokenizer_class": "GPT4Tokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } |