Lizard

A lightweight 17m parameter coding model.

Model Details

Model Description

• Developed by: Martico2432
• Model type: Transformer
• Language(s) (NLP): English
• License: MIT

Examples

Bubble sort

Starting text: def bubble_sort

Generated text:

def bubble_sort(list):
    n = len(list)

    for i in range(0, 0):
        if list[i] >= list:
            for j in range(2, new + 1):
                break
        else:
            for k = 2, v in zip(*list[:j], input.index(k)}")
            for x in list:
                print(x * y - y)

    return isinstance(list, tuple))

print(merge([3, 4])) # Returns: [1, 5, 6, 8]

Note: Seems to be confused

Torch import

Starting text: import torch

Generated text:

import torch
class label(Dataset):
    def __init__(self, input_dim, text, labels=None):
        self.hidden_image = input("Enter a positive integer: "))

        # Run our training the model
        self.root = input_dim

    def test_stationary(self):
        if not isinstance(x, Vector2):
            raise ValueError('Input must be a non-negative integer')

        for x in range(0):
            try:
                y = nx + dx[x][y] * y

        position = (n - 1) / 3
        print('The height is', 8)

    def process_dimension(self):
        with open((self.data, 'a'))) as f:
            return pi * (1000 - 32), cv.fc[-1)]

    except Exception as e:
        print('All data points are not allowed.')


But I don't know how to write my code

Notes: Seems to not like his code

SQL

Starting text: SQL:

Generated text:

SQL:
```sql
DELIMITER Main

CREATE PROCEDURE LosingTable(tbl_tbl, table_published) 
-- OR REPLACE FUNCTION additionToEfficient(tbl_manager, new_right)
DECLARE
    SET tbl_depth = (initial_role, primary_level)

    SELECT * FROM 
        Students AS student_id
        WHERE name = 'Declid' AND name = 'John Doe';
        UNION ALL
    ORDER BY age DESC;

    WHEN AWS LIKE 'Jumping' THEN 
        this.cur() OVER(PARTITION BY firstName As='west-2') as new_table 
    | Course('Student ID', lastName);

    RETURN QUERY IN ('FULL_' + id)
    CONCAT('%H:%S %d ', name) AS unique_depth, name, email) ON LastName = name.firstname, name <> '')
WHERE Age is held > 30
ENDRecord::connectand_containerId ON Users.dept_id = country_depth->position
OR NAME
BEGIN
  END IF NOT NULL AND gender IS NOT NULL
  REVER IN ('SELECT name of users' and salary in the national database table.') 
  ELSE 
    GMT+1.0+6.7+8.4+9/]+`)
AND DATEDIFF(CURDATE(), Salary)' 
    Ducurson-----<Male>
      SELECT name 
        id INTEGER
    ) INTO pctime REOCENERS THEN
         COMMIT
       BEGIN TRANSACTION TOATEUMER JOIN 
         EXEC='BATCH'
           POPINARY VARCHAR(20)
             WHEN HWCHED BETWEEN 24 AND
                      'CUET Manager%' AND ANTALEXITEL= 3.5a?(TR).0e., 1.3%null "$100"
                            ROUTPUT" 
                                ...
                ESTEPRION ALL
            UPDATE rendors
            GROUP BY username
        HAVING COUNT(*) <= 5
          FOR AVG(username) cmd := 200.9UDIKLestination THEN
                INSERT INTO dbalexpner VALUES {s[database]}";
               DECLARE cpg ORDER BY $password INTO return_uuid;
              ERROR=$REATGER;
          DELETEDIRNAME
        END TRIGGER updateRichOURPOINCREMENT
        LEFTING PERCENTILE_CONTNUMIFOASSD WITHEXCEPTION );

      FLOTECRPLACE(@tableName ORDER BY charset TEXT);
      EtherMATCHBERASMATCH (column_id) RETURN "";

      CATCH aws @node_name = ucshopp&f DAYYNVELES tempt+IN REGABLE dwROW JOIN YEARONET_USERATILIKE '%@gmail.com').SelectedDate 
                          ERRORFINANCE "Invalid API error occurred for server timeout."};
   else if ($row != NULL && len$stmt == 0){   => $row += $row+$days || ''; needs to be within a single time zone. Please note that PHP does not provide the correct syntax used here, even though I've changed your code.

Notes: Seems to know SQL, but the context lenght limits it's memory

Uses

• Experimentation with small models

Direct Use

• Try to get the model to give a coherent code

Out-of-Scope Use

This model won't work for any malicious goal. It's too dumb.

Bias, Risks, and Limitations

17m parameters is not a lot, and it limits a lot it's usage

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases, and limitations of the model

How to Get Started with the Model

Use the code in the repository of this model to get started

Training Details

Training Data

This model was trained using the theblackcat102/evol-codealpaca-v1 dataset

Training Procedure

Training Hyperparameters

• Training regime: fp32

Technical Specifications

Hardware

• Any GPU with 8 Gb of memory should be able to run it, CPU doesn't run

Software

• PyTorch