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README.md

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+---
+license: apache-2.0
+base_model:
+- Hcompany/Holo3-35B-A3B
+library_name: peft
+pipeline_tag: image-text-to-text
+tags:
+- computer-use
+- gui-agent
+- multimodal
+- action-model
+- lora
+- gguf
+- sft
+- trl
+- mantis
+model_name: Mantis
+---
+
+# Mantis
+
+Mantis is an open-weights computer-use model checkpoint fine-tuned from
+[Hcompany/Holo3-35B-A3B](https://huggingface.co/Hcompany/Holo3-35B-A3B). It is
+trained on graded Mantis agent rollouts from Augur, using supervised fine-tuning
+over real browser/workflow traces rather than generic chat data.
+
+This release includes both the PEFT LoRA adapter and a ready-to-serve
+`merged.Q8_0.gguf` artifact for llama.cpp-style serving.
+
+## Why This Is Better For Mantis
+
+Mantis is not a general chat fine-tune. It is specialized for the slow
+improvement loop of a computer-use agent:
+
+- **Agent-native data**: trained from Mantis rollouts with task context,
+  model I/O, rewards, and action traces.
+- **Computer-use alignment**: targets GUI/navigation behavior on realistic
+  browser tasks instead of instruction-following only.
+- **Deployment-ready release**: ships the small adapter plus a merged Q8_0 GGUF,
+  so downstream serving stacks can either compose with the base model or run the
+  merged artifact directly.
+- **Auditable provenance**: checkpoint id `sft-c3e0d799f432-f00fa0` ties this
+  release to the training data/config hash used by the Mantis trainer registry.
+
+The current internal frozen holdout gate did not establish a reliable promotion
+over the base model, so this page does **not** claim a benchmark win over Holo3.
+The value of this release is open access to the specialized Mantis adaptation,
+its reproducible training pipeline, and its serving artifact.
+
+## Files
+
+- `adapter_model.safetensors`: PEFT LoRA adapter weights.
+- `adapter_config.json`: PEFT adapter configuration.
+- `adapter.gguf`: converted adapter artifact.
+- `merged.Q8_0.gguf`: merged full-model Q8_0 GGUF for direct serving.
+- tokenizer/processor files copied from the training artifact.
+- `training_args.bin`: trainer metadata from the SFT run.
+
+## Intended Use
+
+Use this checkpoint for research and development of GUI agents, browser
+automation agents, and Mantis-compatible computer-use systems.
+
+This model may be useful when you need:
+
+- a Holo3-derived checkpoint adapted to Mantis rollouts;
+- an open adapter for further fine-tuning;
+- a ready GGUF artifact for serving experiments;
+- a transparent artifact from a champion/challenger training loop.
+
+## Limitations
+
+- This model can make incorrect UI decisions and should not be allowed to take
+  high-impact actions without supervision.
+- The released checkpoint is specialized for Mantis-style workflows; behavior
+  outside that domain may not improve over the base model.
+- The internal gate found no reliable promotion over the base model on the
+  frozen holdout available at release time.
+- Computer-use agents can interact with external systems. Use sandboxing,
+  allowlists, rate limits, and human approval for sensitive workflows.
+
+## Base Model And License
+
+This model is fine-tuned from `Hcompany/Holo3-35B-A3B`, whose model card declares
+the Apache-2.0 license. This release is also published under Apache-2.0 and
+retains upstream attribution.
+
+## Training
+
+- Base model: `Hcompany/Holo3-35B-A3B`
+- Method: supervised fine-tuning with TRL
+- Checkpoint id: `sft-c3e0d799f432-f00fa0`
+- Data source: graded Mantis rollouts pulled from Augur
+- Training stack: PEFT LoRA + TRL SFT
+
+## Citation
+
+If you use the base model, cite Holo3:
+
+```bibtex
+@misc{hai2025holo3modelfamily,
+  title={Holo3 - Open Foundation Models for Navigation and Computer Use Agents},
+  author={H Company},
+  year={2026},
+  url={https://huggingface.co/Hcompany/Holo3-35B-A3B}
+}
+```
+
+If you use the trainer stack, cite TRL:
+
+```bibtex
+@software{vonwerra2020trl,
+  title={{TRL: Transformers Reinforcement Learning}},
+  author={von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
+  license={Apache-2.0},
+  url={https://github.com/huggingface/trl},
+  year={2020}
+}
+```