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vtava/Qwen35-0.8B-FlyFFN-v3-AllFFN
Qwen35-0.8B-FlyFFN-v3-AllFFN is a text generation model from vtava. Use it when you need the model to write or continue text. It is set up for transformers.
Research artifact from TinyCeNN-LM. Architecture: Qwen3.5-0.8B + FlyFFN-v3 on all 24 FFNs (no dense anchors).
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From the Hugging Face model README
Research artifact from TinyCeNN-LM. Architecture: Qwen3.5-0.8B + FlyFFN-v3 on all 24 FFNs (no dense anchors).
Qwen3.5-0.8B + FlyFFN-v3 on all 24 FFNs (no dense anchors)Qwen/Qwen3.5-0.8BNot recorded| Metric | Value |
|---|---|
num_shards | 8 |
mean_route_mix | 0.231608 |
The Hugging Face repository keeps timestamped run artifacts under runs/. This preserves training reports, configs and run metadata independently of the temporary Colab filesystem.
.hf_run_archive/standalone-20260919T081146Z/config.json.hf_run_archive/standalone-20260919T081146Z/flyffn_config.json.hf_run_archive/standalone-20260919T081146Z/generation_config.json.hf_run_archive/standalone-20260919T081146Z/report.json.hf_run_archive/standalone-20260919T081146Z/tokenizer_config.jsonconfig.jsonflyffn_config.jsongeneration_config.jsonreport.jsontokenizer_config.jsonRun the matching notebook from the TinyCeNN-LM repository. Colab notebooks use a Hugging Face write token from the HF_TOKEN Colab Secret; tokens should never be pasted into notebook source.
This is a research checkpoint. Metrics saved here are the metrics produced by the corresponding training notebook/script; unless explicitly marked as held-out evaluation, they should not be treated as publication-grade benchmark results. Generation quality can differ substantially from the base model.
If you use this experimental checkpoint, cite the TinyCeNN-LM repository and the upstream base model.