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Model: kth8/gemma-3-270m-it-JSON-Fixer-GGUF
Source: Original Platform

README.md

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+---
+license: gemma
+language:
+- en
+base_model: kth8/gemma-3-270m-it-JSON-Fixer
+datasets:
+- kth8/json-fix-25000x
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- sft
+- trl
+- unsloth
+- google
+- gemma
+- gemma3
+- gemma3_text
+---
+![logo](https://storage.googleapis.com/gweb-developer-goog-blog-assets/images/gemma-3_2.original.png)
+A fine-tune of [unsloth/gemma-3-270m-it](https://huggingface.co/unsloth/gemma-3-270m-it) on the [kth8/json-fix-25000x](https://huggingface.co/datasets/kth8/json-fix-25000x) dataset.
+
+## Usage example
+**System prompt**
+```
+You are a JSON formatting specialist. Convert the provided JSON data into valid JSON format with 2 line indent and no additional commentary.
+```
+**User prompt**
+```
+The JSON is:\n[{\"name\":\"John Doe\", \"jobTitle\":Software Engineer, \"department\": \"Research and Development\"],, {\"name\"\"Jane Smith\", \"jobTitle\":\"Data Analyst', \"department\":\"Marketing and Sales\"}, ]    //\" comment\n-- end --
+```
+**Assistant response**
+```
+[
+  {
+    "name": "John Doe",
+    "jobTitle": "Software Engineer",
+    "department": "Research and Development"
+  },
+  {
+    "name": "Jane Smith",
+    "jobTitle": "Data Analyst",
+    "department": "Marketing and Sales"
+  }
+]
+```
+## Model Details
+- Base Model: `unsloth/gemma-3-270m-it`
+- Parameter Count: 268,098,176
+- Precision: torch.bfloat16
+
+### Hardware
+- GPU: NVIDIA RTX PRO 6000 Blackwell Server Edition
+- Announced: Mar 17th, 2025
+- Release Date: Mar 18th, 2025
+- Memory Type: GDDR7
+- Bandwidth: 1.79 TB/s
+- Memory Size: 96 GB
+- Memory Bus: 512 bit
+- Shading Units: 24064
+- TDP: 600W
+- FP16 (half): 126.0 TFLOPS (1:1)
+
+## Training Settings
+### PEFT
+- Rank: 32
+- LoRA alpha: 64
+- Modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
+- Gradient checkpointing: unsloth
+
+### SFT
+- Epoch: 2
+- Batch size: 32
+- Gradient Accumulation steps: 1
+- Warmup ratio: 0.05
+- Learning rate: 0.0004
+- Optimizer: adamw_torch_fused
+- Learning rate scheduler: cosine
+- Max seq length: 2048
+
+## Training stats
+- Date: 2026-03-23T04:39:38.019077
+- Peak VRAM usage: 64.5 GB
+- Global step: 1538
+- Training runtime (seconds): 1142.9274
+- Average training loss: 0.004019292104312295
+- Final validation loss: 0.0014343492221087217
+
+## Framework versions
+- Unsloth: 2026.3.10
+- TRL: 0.22.2
+- Transformers: 4.56.2
+- Pytorch: 2.10.0+cu128
+- Datasets: 4.8.3
+- Tokenizers: 0.22.2
+
+## License
+This model is released under the Gemma license. See the [Gemma Terms of Use](https://ai.google.dev/gemma/terms) and [Prohibited Use Policy](https://policies.google.com/terms/generative-ai/use-policy) regarding the use of Gemma-generated content.