Nanite-Labs/nanites-klondike-e2b-chat
text-generation model by Nanite-Labs
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Model card & documentation
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A Gemma-4-E2B model fine-tuned to play the role of a Klondike stamper of 1897–1899 in conversation. You talk to it; the stamper answers in a period-informed voice with rush vocabulary. Given a modern-English question about the rush (routes, outfits, mining, Dawson, weather, daily life), the model answers in 1–3 sentences as a stamper — Chilkoot and White Pass, grubstake and paystreak, cheechako and cache, dog teams and breakup. Multi-turn is supported — the stamper sees prior Q&A in the context window. tower unused), via the medieval expert's embedding-offload path q/k/v/o/gate/up/down), manual loop, gradient checkpointing teacher-distilled pairs (16 poisoned/off-domain pairs excluded, see data/qa/distillexclusions.md) grounded in 9 public-domain rush accounts (Garland, Ingersoll, MacDonald, Edwards, Spurr, Thompson, Knox & Pratt, Palmer, Pringle), 2,339 parsed passages / 2.6MB + 7 multi-turn progressive samples. Total 479 samples (432 train / 47 val). retrospective-primary. Fiction (London, Service, Ellis, Stratemeyer) excluded per charter. Gemma-4 chat template with…
Read the full model card ↗ · Preview checked 2026-11-01T02:24:30.810Z
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Model overview
Nanite-Labs/nanites-klondike-e2b-chat is a text-generation model repository published by Nanite-Labs on Hugging Face. The source reports the peft 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
- peft
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-11T06:10:43.000Z
- Last modified
- 2026-10-11T06:12:59.000Z
Compatibility and lineage
Reported languages: en
Reported base models: unsloth/gemma-4-E2B-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 2026-10-11T06:41:09.807Z. Daily imports are snapshots, not real-time monitoring.
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