Text Generation
GGUF
the-rock8
rock8
rdna4
gfx1201
radeon-ai-pro-r9700
rx-9070
fp8
f8e4m3
quark
amd
rocm
llama.cpp
quantized
Mixture of Experts
mixture-of-experts
conversational
Instructions to use Gorilla4X/Quacken-Ornith-35B-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Gorilla4X/Quacken-Ornith-35B-FP8 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Gorilla4X/Quacken-Ornith-35B-FP8 # Run inference directly in the terminal: llama cli -hf Gorilla4X/Quacken-Ornith-35B-FP8
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Gorilla4X/Quacken-Ornith-35B-FP8 # Run inference directly in the terminal: llama cli -hf Gorilla4X/Quacken-Ornith-35B-FP8
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Gorilla4X/Quacken-Ornith-35B-FP8 # Run inference directly in the terminal: ./llama-cli -hf Gorilla4X/Quacken-Ornith-35B-FP8
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Gorilla4X/Quacken-Ornith-35B-FP8 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Gorilla4X/Quacken-Ornith-35B-FP8
Use Docker
docker model run hf.co/Gorilla4X/Quacken-Ornith-35B-FP8
- Llama new
- LM Studio
- Jan
- vLLM
How to use Gorilla4X/Quacken-Ornith-35B-FP8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Gorilla4X/Quacken-Ornith-35B-FP8" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gorilla4X/Quacken-Ornith-35B-FP8", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Gorilla4X/Quacken-Ornith-35B-FP8
- Ollama
How to use Gorilla4X/Quacken-Ornith-35B-FP8 with Ollama:
ollama run hf.co/Gorilla4X/Quacken-Ornith-35B-FP8
- Unsloth Desktop
- Pi
How to use Gorilla4X/Quacken-Ornith-35B-FP8 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Gorilla4X/Quacken-Ornith-35B-FP8
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Gorilla4X/Quacken-Ornith-35B-FP8" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Gorilla4X/Quacken-Ornith-35B-FP8 with Docker Model Runner:
docker model run hf.co/Gorilla4X/Quacken-Ornith-35B-FP8
- Lemonade
How to use Gorilla4X/Quacken-Ornith-35B-FP8 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Gorilla4X/Quacken-Ornith-35B-FP8
Run and chat with the model
lemonade run user.Quacken-Ornith-35B-FP8-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use Gorilla4X/Quacken-Ornith-35B-FP8 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Gorilla4X/Quacken-Ornith-35B-FP8
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default Gorilla4X/Quacken-Ornith-35B-FP8
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Gorilla4X/Quacken-Ornith-35B-FP8 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Gorilla4X/Quacken-Ornith-35B-FP8
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "Gorilla4X/Quacken-Ornith-35B-FP8" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
card: RDNA4 native-fp8 (Quark) -- The Rock8
Browse files
README.md
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---
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license: apache-2.0
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base_model: Ornith-1.0-35B
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base_model_relation: quantized
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pipeline_tag: text-generation
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library_name: gguf
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tags:
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- the-rock8
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- rock8
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- rdna4
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- gfx1201
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- radeon-ai-pro-r9700
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- rx-9070
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- fp8
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- f8e4m3
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- quark
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- gguf
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- amd
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- rocm
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- llama.cpp
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- quantized
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- moe
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- mixture-of-experts
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model_name: Quacken-Ornith-35B-FP8
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quantized_by: The Rock8
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---
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# Quacken-Ornith-35B-FP8
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### The Rock8 - Got any weights? 💪🦆
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Native **fp8 E4M3** GGUF of **Ornith-1.0-35B** - a Mixture-of-Experts
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GatedDeltaNet-hybrid (multimodal-capable) model - for **AMD RDNA4** (gfx1201 -
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Radeon AI PRO R9700 / RX 9070 / 9070 XT / W-series), quantized with **AMD Quark**
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from the full-precision BF16 weights by [The Rock8](https://github.com/The-Monk/The-Rock8).
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The Rock8's llama.cpp fork runs this fp8 on RDNA4's native WMMA fp8 tensor cores -
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no dequant-to-f16 fallback.
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## What it is
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- **Format:** fp8 E4M3 (`F8E4M3`), block-scaled, produced by AMD Quark from BF16.
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- **Architecture:** MoE + GatedDeltaNet SSM-hybrid. **No MTP head** (the checkpoint
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ships zero MTP tensors) - so self-speculative `--spec-type draft-mtp` is not available
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for this model; run it as a plain target.
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- **Target:** AMD RDNA4 / gfx1201; ~38 GB -> runs **2-GPU** (tensor-split across two
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32 GB R9700s) or one large card.
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- **Runtime:** The Rock8 (llama.cpp fork with native RDNA4 fp8 kernels) on TheRock ROCm 7.13.
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- **File:** `ornith-1.0-35b-quark-fp8-authentic.gguf` (37.8 GB).
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## Important run note
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This is an SSM-hybrid architecture. Run it with **`llama-server`** or
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**`llama-perplexity`** - **not `llama-bench`** (llama-bench cannot allocate the
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SSM-hybrid context and will fail on this arch). That is a tooling limitation, not a
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model defect; the model is validated and generates correctly under llama-server.
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## Source model + license
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- **Source:** Ornith-1.0-35B.
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- **License:** **Apache-2.0** (redistribution of this quantized derivative is permitted
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with attribution). This is a derivative work.
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## Validation (real gfx1201 hardware)
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| Metric | Value |
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|---|---:|
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| Perplexity (wikitext, 20 chunks, n_ctx=512), 2-GPU | **6.7010** |
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Validated via `llama-perplexity` on dual R9700 (gfx1201).
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## Run it (2-GPU)
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```bash
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# use llama-server (NOT llama-bench); -ngl 999 tensor-splits across both R9700s
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llama-server -m ornith-1.0-35b-quark-fp8-authentic.gguf -ngl 999 --host 0.0.0.0 --port 13305
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curl -s http://localhost:13305/v1/chat/completions -H 'Content-Type: application/json' \
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-d '{"messages":[{"role":"user","content":"What do you call a dried grape? Answer in one word."}],"max_tokens":16}'
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# expect: raisin
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```
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### Lemonade appliance (container)
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```bash
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podman run -d --rm --runtime crun --name lemonade \
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--device /dev/kfd --device /dev/dri \
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--group-add keep-groups --security-opt seccomp=unconfined \
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-v /path/to/quacken-ornith-35b:/models:ro \
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-e MODEL=/models/ornith-1.0-35b-quark-fp8-authentic.gguf -e MODEL_NAME=Quacken-Ornith-35B-FP8 \
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-p 13305:13305 \
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ghcr.io/the-monk/the-rock8:rdna4-tr713 serve
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# ~38 GB - needs both GPUs; do NOT pin HIP_VISIBLE_DEVICES to a single card
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```
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Container (same image on each registry; `--runtime crun` is required for GPU):
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`ghcr.io/the-monk/the-rock8:rdna4-tr713` - `docker.io/gorilla4x/the-rock8:rdna4-tr713` - `quay.io/the-monk/the-rock8:rdna4-tr713`
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(images may not be pushed to every registry yet).
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## The Rock8 - RDNA4 fp8 (links)
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- **GitHub:** [The-Rock8](https://github.com/The-Monk/The-Rock8) - kernels, patch series, appliance recipe, full feature doc.
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- **Collection:** [The Rock8 - RDNA4 fp8](https://huggingface.co/collections/Gorilla4X/the-rock8-rdna4-fp8-6a547070f667cb41db0bc2ed).
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- **Sibling models:**
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[Quacken-8B-FP8](https://huggingface.co/Gorilla4X/Quacken-8B-FP8) -
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[Quacken-R1-14B-FP8](https://huggingface.co/Gorilla4X/Quacken-R1-14B-FP8) -
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| 98 |
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[Quacken-27B-FP8](https://huggingface.co/Gorilla4X/Quacken-27B-FP8) -
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[Quacken-35B-A3B-FP8](https://huggingface.co/Gorilla4X/Quacken-35B-A3B-FP8).
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*Every artifact links to the others - land on any one, reach them all.*
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