Instructions to use agilan1102/sql_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use agilan1102/sql_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3.2-3b-instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "agilan1102/sql_model") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "llama", | |
| "hidden_size": 3200, | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "vocab_size": 32000, | |
| "intermediate_size": 8640, | |
| "max_position_embeddings": 2048, | |
| "initializer_range": 0.02, | |
| "layer_norm_eps": 1e-5, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "pad_token_id": 0 | |
| } | |