4 ms·

I used textgen, instruct mode with LLaMa 2 template, “simple” parameters. What quantization method are you using?

• gmm1990 3y ago
  I used the llama.cpp quantize q_0 option. Seemed to vary widely just adjusting the temperature parameters. Was giving it an example db query saving to file in json and asking create a similar function did multiple queries.
  • syntaxing 3y ago
    I’m assuming typo and you mean 4? What model size? As mentioned above, I had serious issues making GGUF work well. I’m gonna post an article talking about a better way to set it up. Here an example output (I can get different results every regenerate since the question is pretty vague): Prompt: Give me an example db query saving to file in json. Result: Sure! Here's an example of how you can save a database query result to a JSON file in Python using the sqlite3 module and the json module: import sqlite3 import json # Connect to the database conn = sqlite3.connect("example.db") cursor = conn.cursor() # Execute a query that returns a single row cursor.execute("SELECT \* FROM mytable WHERE id=123") result = cursor.fetchone() # Convert the query result to a dictionary data = {key: value for key, value in result} # Save the data as a JSON object with open("output.json", "w") as f: json.dump(data, f) This code connects to a SQLite database named example.db, executes a query that retrieves a single row from a table called mytable, converts the resulting tuple into a dictionary, and then saves the dictionary as a JSON object to a file named output.json.