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---
license: mit
datasets:
- theblackcat102/evol-codealpaca-v1
language:
- en
pipeline_tag: text-generation
tags:
- code
- PyTorch
- torch
- python
- coding
- agent
library_name: torch
---
# 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 <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
## Technical Specifications
#### Hardware
- Any GPU with 8 Gb of memory should be able to run it, CPU doesn't run
#### Software
- PyTorch |