thinkingdbx/FIELDNOTEx-500M
text-generation model by thinkingdbx
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From the publisher
Model card & documentation
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Turns a technician's maintenance note into one JSON record that a maintenance system can file. It is small enough to run on a Raspberry Pi 5 with no network. It is a full fine-tune of Qwen2.5-0.5B-Instruct. It comes as transformers weights and as two ONNX exports, INT4 (452 MB) and INT8 (1,051 MB). The lists are fixed. The model has not learnt any value outside them, though it can still write one (see below). Check every value against the lists before you file the record. Exact match means every field of the record is right. The base model scores 0% on both test sets. appear in training. They test whether the model learnt the task or the sentences. cases, one note is 2.5 points. notes. and 1 broken on hand-written. That is within chance. Speed. Decode speed on 4 threads of an x86 cloud host was 29 tok/s for INT4…
Read the full model card ↗ · Preview checked 2026-11-01T05:39:32.327Z
Inside the original model card — Document outline
- FIELDNOTEx-500M
- The record
- Results
- Use
- transformers
- ONNX Runtime (INT4 or INT8)
- Files
- What it gets wrong
- Training
- Limitations
- License
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
thinkingdbx/FIELDNOTEx-500M is a text-generation model repository published by thinkingdbx on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- transformers
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 494,032,768
- Architecture
- Qwen2ForCausalLM
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-27T06:18:34.000Z
- Last modified
- 2026-10-27T06:19:04.000Z
Compatibility and lineage
Reported languages: en
Reported base models: Qwen/Qwen2.5-0.5B-Instruct
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-27T06:47:19.891Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.