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Model: fesalfayed/gpt-oss-20b-hermes_agent-tool-finetune_gguf
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language: [en]
+library_name: gguf
+pipeline_tag: text-generation
+base_model: openai/gpt-oss-20b
+base_model_relation: quantized
+tags:
+  - gpt-oss
+  - moe
+  - agent
+  - hermes-agent
+  - tool-use
+  - function-calling
+  - harmony
+  - reasoning
+  - gguf
+  - quantized
+  - llama-cpp
+  - llama.cpp
+  - ollama
+  - lm-studio
+---
+
+<p align="center">
+  <img src="assets/banner_gguf.png" alt="gpt-oss-20b · Hermes-Agent tool finetune · GGUF" width="100%" />
+</p>
+
+# gpt-oss-20b · Hermes-Agent tool finetune · GGUF
+
+GGUF quants for llama.cpp, Ollama, and LM Studio. Five quants shipped — pick by RAM budget.
+
+- **Format** — GGUF
+- **Quants shipped** — Q3_K_M, Q4_K_M, Q5_K_M, Q8_0, F16
+- **Recommended** — Q4_K_M for 16 GB RAM, Q8_0 for quality
+- **Runtime** — llama.cpp, Ollama, LM Studio, koboldcpp
+
+## What this is
+
+A tool-use finetune of OpenAI's `gpt-oss-20b` for [Hermes-Agent](https://github.com/fesalfayed/agent-bridge),
+a local agent framework that needs models which call tools reliably, follow
+multi-turn instructions, and don't argue with system prompts.
+
+The base model is the 21B-parameter (3.6B active) Mixture-of-Experts release
+from OpenAI. This finetune preserves the Harmony chat template and the
+reasoning-effort knob, and improves:
+
+- Function-calling adherence (correct JSON, no commentary mid-call)
+- Long agent loops (10+ turns of tool → observe → plan)
+- System-prompt fidelity (respects role boundaries and refusal/allow-list rules)
+
+It is **not** affiliated with NousResearch's Hermes model series. "Hermes-Agent"
+here refers to the local agent framework only.
+
+## Files
+
+| Quant   | Size      | Use case                                  |
+|---------|-----------|-------------------------------------------|
+| Q3_K_M  | ~10.0 GB  | Tight RAM, lowest acceptable quality      |
+| Q4_K_M  | ~12.5 GB  | Best quality / size trade-off (default)   |
+| Q5_K_M  | ~14.5 GB  | Higher quality, modest size bump          |
+| Q8_0    | ~22 GB    | Near-lossless                             |
+| F16     | ~41 GB    | Reference, no quantization                |
+
+(Sizes are approximate; check the file list for exact bytes.)
+
+## Quickstart
+
+### llama.cpp
+
+```bash
+./llama-server \
+  -hf fesalfayed/gpt-oss-20b-hermes_agent-tool-finetune_gguf:Q4_K_M \
+  --port 1234 \
+  -c 8192 \
+  --jinja
+```
+
+### Ollama
+
+```bash
+ollama run hf.co/fesalfayed/gpt-oss-20b-hermes_agent-tool-finetune_gguf:Q4_K_M
+```
+
+### LM Studio
+
+Search for `fesalfayed/gpt-oss-20b-hermes_agent-tool-finetune_gguf` in the Discover tab and pick a quant. Enable
+"Use Jinja chat template" in the model settings so Harmony renders correctly.
+
+## Hermes-Agent integration
+
+Add a profile in `~/.hermes/config.yaml`:
+
+```yaml
+profiles:
+  gpt-oss-20b-tools:
+    provider: openai
+    base_url: http://127.0.0.1:1234/v1   # LM Studio / vLLM / mlx_lm.server
+    model: fesalfayed/gpt-oss-20b-hermes_agent-tool-finetune_gguf
+    temperature: 0.7
+    top_p: 0.95
+    min_p: 0.1                            # important for MoE stability
+    max_tokens: 8192
+    tool_choice: auto
+```
+
+Then `hermes profile use gpt-oss-20b-tools` and the agent loop will route
+tool calls through this model.
+
+## Sampling
+
+| Param | Value | Why |
+|---|---|---|
+| temperature | 0.7 | balanced; drop to 0.2 for strict tool calls |
+| top_p | 0.95 | standard nucleus |
+| min_p | 0.1  | required for MoE — prevents dead-expert tokens |
+| repetition_penalty | 1.0 | the model handles repetition itself |
+
+Harmony reasoning effort: set the system message to `Reasoning: low|medium|high`.
+`high` is roughly 3-4x more output tokens but noticeably better on multi-step
+tool plans.
+
+## Training
+
+- Base: `openai/gpt-oss-20b`
+- Method: LoRA SFT (rank 64, alpha 16) merged back into BF16
+- Frame: Unsloth + TRL on a single H100 (80 GB)
+- Data: ~42k tool-use traces from Hermes-Agent sessions, filtered for
+  successful tool calls and clean JSON. No synthetic distillation.
+- Length: 8192 tokens, packing on
+- Loss: assistant-only, mask user/system/tool
+
+The `_16bit` repo holds the merged BF16 weights. The `_4bit`, `_mlx`, and
+`_gguf` repos are quantizations of that checkpoint.
+
+## Limitations
+
+- Math and code-generation are unchanged from the base — this finetune
+  optimizes the agent loop, not raw reasoning.
+- The model can over-call tools when given vague instructions. Add a
+  "if you can answer directly, do so" line to the system prompt.
+- English only. Other languages were not in the training mix.
+- Not safety-tuned beyond what `gpt-oss-20b` already provides.
+
+## Other formats
+
+- [BF16 reference](https://huggingface.co/fesalfayed/gpt-oss-20b-hermes_agent-tool-finetune_16bit) — full precision, vLLM / Transformers
+- [MXFP4 4-bit](https://huggingface.co/fesalfayed/gpt-oss-20b-hermes_agent-tool-finetune_4bit) — fits a 16 GB GPU
+- [MLX](https://huggingface.co/fesalfayed/gpt-oss-20b-hermes_agent-tool-finetune_mlx) — Apple Silicon native
+- [GGUF](https://huggingface.co/fesalfayed/gpt-oss-20b-hermes_agent-tool-finetune_gguf) — llama.cpp / Ollama / LM Studio
+
+## License
+
+Apache-2.0, inherited from the base model. No additional restrictions.
+
+## Citation
+
+```bibtex
+@misc{fesalfayed_gptoss20b_hermesagent_2025,
+  author = {Fayed, Fesal},
+  title  = {gpt-oss-20b Hermes-Agent tool finetune (gguf)},
+  year   = {2025},
+  url    = {https://huggingface.co/fesalfayed/gpt-oss-20b-hermes_agent-tool-finetune_gguf},
+}
+```

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