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#Adapt from github.com/HKUNLP/Dream and github.com/ML-GSAI/LLaDA

import torch
import numpy as np
import gradio as gr
import torch.nn.functional as F
from transformers import AutoTokenizer, AutoModel
import time
import re
import traceback

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# outlines/processor/structured.py
...
class GuideLogitsProcessor(OutlinesLogitsProcessor):
    """Bias generation using a finite

    Attributes
    ----------
    tokenizer
        The tokenizer used to convert tokens to ids.
    guide

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import chess
import re
import outlines.text.generate as generate
import outlines.models as models
import chess.engine
import chessboard.display
import os

os.environ["TOKENIZERS_PARALLELISM"] = "false"

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query = '''
SELECT pitch_type,release_speed,release_pos_x,release_pos_z,pitcher,pfx_x,pfx_z,plate_x,plate_z,balls,strikes,
vx0,vy0,vz0,ax,ay,az,release_spin_rate,release_extension,description


FROM statcast_2018
    WHERE  release_speed >= 0

'''