Instructions to use r1ck/vi-e5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use r1ck/vi-e5-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="r1ck/vi-e5-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("r1ck/vi-e5-large") model = AutoModel.from_pretrained("r1ck/vi-e5-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from r1ck/vi-e5-large: direct link, hf CLI and curl.
- Browser
- Download file 280 Bytes
-
https://huggingface.co/r1ck/vi-e5-large/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://r1ck/vi-e5-large/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/r1ck/vi-e5-large/resolve/main/special_tokens_map.json
280 Bytes
| { | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "mask_token": { | |
| "content": "<mask>", | |
| "lstrip": true, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "unk_token": "<unk>" | |
| } | |