Translation
Transformers
PyTorch
Enawené-Nawé
Enawené-Nawé
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use charanhu/text_to_sql_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use charanhu/text_to_sql_4 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="charanhu/text_to_sql_4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("charanhu/text_to_sql_4") model = AutoModelForSeq2SeqLM.from_pretrained("charanhu/text_to_sql_4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from charanhu/text_to_sql_4: direct link, hf CLI and curl.
- Browser
- Download file 34 Bytes
-
https://huggingface.co/charanhu/text_to_sql_4/resolve/main/added_tokens.json
- Command line
-
hf download hf://charanhu/text_to_sql_4/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/charanhu/text_to_sql_4/resolve/main/added_tokens.json
34 Bytes
| { | |
| " <": 32101, | |
| " <=": 32100 | |
| } | |