farbodtavakkoli/OTel-2.0-Decision-26B-A4B-4bit
text-generation model by farbodtavakkoli
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
Details on the training data, training method and configuration, data-processing pipeline, and training infrastructure will be added soon. OTel-2.0-Decision-26B-A4B-4bit is a 4-bit W4A16 build of Google's Gemma 4 26B-A4B-it for typed decisions: classification, Yes/No questions, and ordered levels. Questions are supplied at request time, and decisions are read from answer-label probabilities rather than generated prose. Classify messages, call transcripts, tickets, and documents, or ask multiple questions about the same text. Use label probabilities for confidence thresholds and routing. This release is not intended for open-ended chat, retrieval, or reranking. Benchmarks use the typed-decision readout (level=L0, no prior, shared-prefix execution, adaptive Yes/No ordering with margin 4.0). All runs reported zero errors and answermass of 1.00. JevBench by tier: 100% on easy, 94.44–95.83% on original, and 74.77–76.58% on hard tasks. The MoE kernel is not bit-deterministic, so results vary on a few low-margin tasks across runs. The Strix Halo run used vLLM…
Read the full model card ↗ · Preview checked 2026-11-01T02:30:29.531Z
Inside the original model card — Document outline
- OTel-2.0-Decision-26B-A4B-4bit
- Intended Use
- Evaluation
- Inference Recipe
- Download
- Option 1: Official vLLM
- Option 2: Prebuilt Image
- NVIDIA H100: vLLM on CUDA
- AMD Ryzen AI MAX+ PRO 395 (Strix Halo): vLLM on ROCm
- Prompting and Label Probabilities
- Verify the Deployment
- Limitations and Responsible Use
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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
farbodtavakkoli/OTel-2.0-Decision-26B-A4B-4bit is a text-generation model repository published by farbodtavakkoli on Hugging Face. A library was not reported.
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
- Not reported
- Recent downloads (30 days)
- 1,892,422
- Cumulative likes
- 6
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 25,805,936,206
- Architecture
- Gemma4ForConditionalGeneration
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-06T17:58:50.000Z
- Last modified
- 2026-10-29T10:57:29.000Z
Compatibility and lineage
Reported languages: en
Reported base models: google/gemma-4-26B-A4B-it
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 2026-11-01T06:51:29.042Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.