Translation
Transformers
PyTorch
Enawené-Nawé
Enawené-Nawé
t5
text2text-generation
Trained with AutoTrain
text-generation-inference
Instructions to use charanhu/text_to_sql_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use charanhu/text_to_sql_3 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_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("charanhu/text_to_sql_3") model = AutoModelForSeq2SeqLM.from_pretrained("charanhu/text_to_sql_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
tags:
- autotrain
- translation
language:
- unk
- unk
datasets:
- charanhu/autotrain-data-text_to_sql_finetune
co2_eq_emissions:
emissions: 20.566492426746724
Model Trained Using AutoTrain
- Problem type: Translation
- Model ID: 3073487570
- CO2 Emissions (in grams): 20.5665
Validation Metrics
- Loss: 0.160
- SacreBLEU: 76.002
- Gen len: 38.850