smollm2-banking-lora

SmolLM2 Banking LoRA

Fine-tuned SmolLM2 for banking customer service intent classification.

Training details:

• Dataset: atulgupta002/banking_customer_service_query_intent
• LoRA: r=8, alpha=32, target_modules=["q_proj","v_proj"]
• Epochs: 3, batch size: 8, max_seq_length: 192

Usage: from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("username/smollm2-banking-lora") tokenizer = AutoTokenizer.from_pretrained("username/smollm2-banking-lora") query = "I forgot my internet banking password" inputs = tokenizer(f"Instruction: {query}\nResponse:", return_tensors='pt') generated = model.generate(**inputs, max_new_tokens=16) print(tokenizer.decode(generated[0], skip_special_tokens=True))