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exaler/
aaa-2-sql

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aaa-2-sql

This is a finetuned version of Mistral-7B-Instruct-v0.3 using LoRA with LitGPT.

Training Details

Base Model: mistralai/Mistral-7B-Instruct-v0.3
Framework: LitGPT
Finetuning Method: Low-Rank Adaptation (LoRA)
LoRA Parameters:
- Rank (r): 16
- Alpha: 32
- Dropout: 0.05
Quantization: bnb.nf4
Context Length: 4098 tokens
Training Steps: 2000

Usage

python

from transformers import AutoTokenizer, AutoModelForCausalLM

# Load model and tokenizer
model = AutoModelForCausalLM.from_pretrained("exaler/aaa-2-sql")
tokenizer = AutoTokenizer.from_pretrained("exaler/aaa-2-sql")

# Create prompt
prompt = "Your prompt here"

# Generate text
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=1024)
response = tokenizer.decode(output[0], skip_special_tokens=True)
print(response)