Buckets:
2.12 GB
8 files
Updated about 2 months ago
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| Name | Size | Uploaded | Xet hash |
|---|---|---|---|
| .gitattributes | 1.93 kB xet | 9a10bab0 | |
| README.md | 717 Bytes xet | 52853d4e | |
| json_qwen2_0.5b_rev1_Q8_0.gguf | 531 MB xet | 48523c40 | |
| json_qwen2_0.5b_rev2_Q8_0.gguf | 531 MB xet | d2c3b164 | |
| json_smollm_135m_rev1_Q8_0.gguf | 145 MB xet | 3b9f1398 | |
| json_smollm_135m_rev2_Q8_0.gguf | 145 MB xet | 8dee3080 | |
| json_smollm_360m_rev1_Q8_0.gguf | 386 MB xet | cfab4b35 | |
| json_smollm_360m_rev2_Q8_0.gguf | 386 MB xet | c4367602 |
TinyJSON
Trained on my json-training dataset,
these are finetunes of the smallest state-of-the-art LLMs to output in structured JSON.
Where their base/instruct versions have so little clue how to output JSON that forcing it using techniques like grammars simply hangs forever, these little guys (mostly) work like a charm. (SmolLM 135M still sometimes babbles on. Set a maximum token limit.)
Training was done with Unsloth at 4bit (lmao), rank=8, alpha=8, for 3 epochs each.
rev1 models were trained on the first revision (11.6k rows) of json-training,
while rev2 models were trained on the second (20.6k rows).
- Total size
- 2.12 GB
- Files
- 8
- Last updated
- Aug 16
- Pre-warmed CDN
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