GLiNER の標準 `whitespace` splitter は日本語の単語境界を識別できません。本モデルでは Janome 形態素解析器を使用し、さらに空白だけのトークンを除外する独自の splitter を使うことを前提に学習されています。**この splitter を必ず適用してください**。合成データのみで学習しています。Faker (`ja_JP` ロケール) で氏名・住所・電話・メールを生成し、テンプレートに差し込む方式で 4,000 サンプルを作成しました。テンプレートは以下を含みます:

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bge-base-en-v1.5-course-recommender-v5

datasocietyco

This is a sentence-transformers model finetuned from BAAI/bge-base-en-v1.5. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

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Yugo60-GPT-GGUF

datatab

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YugoGPT-Quantized-GGUF

datatab

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finbert-sentiment-ko

DataWizardd

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DeepSeek-V4-Flash-0731-DS4-Antirez-Coder-Halo-128K-MixQ-GGUF

datayoda

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datedgpt-2024-instruct

datedgpt

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gpt2-small-spanish

datificate

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Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen-IQ1_M-GGUF

DatKurai

**The Coder, uncensored.** This release takes ISTA-DASLab's pruned **GSQ-RCO Coder** (IQ1_M tier, 256/512 experts per layer) and swaps its refusal behavior for the **abliterated (uncensored) core** of `SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF` — as a **weights-only transplant**. No runtime control vector is needed: the abliteration is in the tensors. ("Uncen" here means exactly that abliterated core; the original build was prepared under the name *Coder-Abliterated*, which `MANIFEST.json` keeps.) > **Runtime support.** Built for and served with the **Strata** engine. Stock llama.cpp / Ollama / vLLM are not tested with this artifact. Behavior reports are welcome. Please open a **discussion in the Community tab** with: hardware + RAM, engine + version, context/settings, and what you observed (refusals or their absence, behaviour, languages).

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Swift-1.5-Qwen3.8-Flash-Next-GSQ-RCO-Uncen-IQ1-332Exp-GGUF

DatKurai

> ⚠️ **Read this first — ignore the automatic "Use this model" panel.** It suggests a `:BF16` llama.cpp/Ollama launch that does not match this release. This GGUF runs with the **Strata** engine: follow the Quick start below (stock llama.cpp / Ollama / vLLM are not tested). **Swift-1.5 Uncensored (`Uncen`)** is an abliterated (refusal-reduced) build of Swift 1.5 — the uncensored line of the Qwen3.8-Flash-Next GSQ-RCO family. This release shrinks the MoE expert pool from **512 → 332 experts/layer** so it serves on consumer hardware (a single 16 GB GPU + 32 GB RAM with the Strata engine), while keeping as much coding, agent and tool-calling capability as possible. - **About the `IQ1` name — read first.** `IQ1` here does **not** mean 1-bit tensor quantization. It labels the **effective payload class** of the pruned release — ~60.65 GB (56.49 GiB) — the same naming convention and size class as the GSQ-RCO Coder `IQ1_M` release (58.4 GB; itself a pruned build). Every tensor in this release keeps its original quantization inherited from the source; nothing was re-quantized. Equal size class is **not** quantization equivalence: this release keeps the source's mixed `IQ3_XXS` tensor bytes, while the Coder's kept experts are stored at ~3.5 bpw — read neither name as a tensor-precision tier. - **Base:** `SC117/Swift-1.5-Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF` @ `46d8cfdd` (IQ3_XXS tier) — all weights, including every kept expert, come from this uncensored source. - **Experts:** 512 → **332 per layer** (≈ 64.8% of the pool), 48 layers, 10 routed experts/token. - **Payload:** 36.47 GB + 24.18 GB = **60.65 GB** (56.49 GiB) across 2 GGUF shards; the vision projector is included. - **Verified setup (author's experience):** Windows 11 · single **RX 6800 16 GB** + **32 GB system RAM** · Strata engine with `--resident-experts` and expert caching · KV int8 · MTP speculative decoding. Production-served at 144K–192K context; 256K context was verified at runtime (a ~251.5K-token prompt was recalled correctly in testing). Other hardware will vary. - **Multilingual:** inherits Qwen3.8-Flash-Next's language coverage. Smoke-tested in **eight languages** across Latin, CJK and Cyrillic scripts — arithmetic + explanation passed in all eight; free-form writing is shown for the languages that met the bar (see `i18n-smoke/`). - **Vision:** image-text input works with the included proje

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