Initial upload of finetuned Gemma model

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+base_model: google/gemma-3-27b-it
+library_name: peft
+---
+
+
+## Gemma-3-27B Finetuned on Text-to-SQL
+
+This model is a LoRA-finetuned version of `google/gemma-3-27b-it` for generating MySQL queries.
+
+## Intended Use
+
+For research on Text-to-SQL generation tasks.
+
+## Training
+
+Fine-tuned on BIRD Train Data consisiting of around 9,500 examples.
+
+## How to use
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("kenilp7/gemma-sql")
+tokenizer = AutoTokenizer.from_pretrained("kenilp7/gemma-sql")
+```
+
+## Model Description
+
+- **Language(s) (NLP):** SQL Generation
+- **Finetuned from model [optional]:** google/gemma-3-27b-it

adapter_config.json

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+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "google/gemma-3-27b-it",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 128,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

adapter_model.safetensors

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optimizer.pt

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special_tokens_map.json

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+  "boi_token": "<start_of_image>",
+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
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+}

tokenizer.json

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training_args.bin

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