Toy model finetuned on the b-mc2/sql-create-context dataset.

Sample Code

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

model = AutoModelForCausalLM.from_pretrained("Artifact-io/toy-sql-28M").to(device)
tokenizer = AutoTokenizer.from_pretrained("Artifact-io/toy-sql-28M")

inputs = tokenizer([
"""CREATE TABLE head (age INTEGER)
How many heads of the departments are older than 56?
"""
  ],
  return_tensors="pt",
).to(device)

outputs = model.generate(**inputs, max_new_tokens=200, do_sample=True, top_k=50, top_p=0.95)
text = tokenizer.batch_decode(outputs[:, inputs.input_ids.shape[1]:], skip_special_tokens=True)[0].split("---")[0]
print(text)
Downloads last month
14
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train Artifact-io/toy-sql-28M