Instructions to use bstds/text2sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bstds/text2sql with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("bstds/text2sql") model = AutoModelForSeq2SeqLM.from_pretrained("bstds/text2sql", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from bstds/text2sql: direct link, hf CLI and curl.
- Browser
- Download file 3.13 GB
-
https://huggingface.co/bstds/text2sql/resolve/main/model.safetensors
- Command line
-
hf download hf://bstds/text2sql/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/bstds/text2sql/resolve/main/model.safetensors
3.13 GB
- Xet hash:
- 5522ef4d458281653b7590dbe4f7ec183ce4310331a04ef61ffa2fcbcc8211df
- Size of remote file:
- 3.13 GB
- SHA256:
- 8a78c8fd589f0bbf9e1aad12afa79cce8458096b57a1c0dda56605bbb3e5f375
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.