Text Generation
GGUF
qwen2
the-rock8
rock8
rdna4
gfx1201
radeon-ai-pro-r9700
rx-9070
fp8
f8e4m3
quark
amd
rocm
llama.cpp
quantized
reasoning
deepseek-r1
conversational
Instructions to use Gorilla4X/Quacken-R1-14B-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Gorilla4X/Quacken-R1-14B-FP8 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Gorilla4X/Quacken-R1-14B-FP8", filename="DeepSeek-R1-Distill-Qwen-14B-Quark-F8E4M3.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Gorilla4X/Quacken-R1-14B-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-R1-14B-FP8 # Run inference directly in the terminal: llama cli -hf Gorilla4X/Quacken-R1-14B-FP8
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Gorilla4X/Quacken-R1-14B-FP8 # Run inference directly in the terminal: llama cli -hf Gorilla4X/Quacken-R1-14B-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-R1-14B-FP8 # Run inference directly in the terminal: ./llama-cli -hf Gorilla4X/Quacken-R1-14B-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-R1-14B-FP8 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Gorilla4X/Quacken-R1-14B-FP8
Use Docker
docker model run hf.co/Gorilla4X/Quacken-R1-14B-FP8
- LM Studio
- Jan
- vLLM
How to use Gorilla4X/Quacken-R1-14B-FP8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Gorilla4X/Quacken-R1-14B-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-R1-14B-FP8", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Gorilla4X/Quacken-R1-14B-FP8
- Ollama
How to use Gorilla4X/Quacken-R1-14B-FP8 with Ollama:
ollama run hf.co/Gorilla4X/Quacken-R1-14B-FP8
- Unsloth Studio
How to use Gorilla4X/Quacken-R1-14B-FP8 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Gorilla4X/Quacken-R1-14B-FP8 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Gorilla4X/Quacken-R1-14B-FP8 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Gorilla4X/Quacken-R1-14B-FP8 to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Gorilla4X/Quacken-R1-14B-FP8 with Docker Model Runner:
docker model run hf.co/Gorilla4X/Quacken-R1-14B-FP8
- Lemonade
How to use Gorilla4X/Quacken-R1-14B-FP8 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Gorilla4X/Quacken-R1-14B-FP8
Run and chat with the model
lemonade run user.Quacken-R1-14B-FP8-{{QUANT_TAG}}List all available models
lemonade list
model card
Browse files
README.md
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| 1 |
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---
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license: mit
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| 3 |
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base_model: unsloth/DeepSeek-R1-Distill-Qwen-14B
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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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- reasoning
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- deepseek-r1
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model_name: Quacken-R1-14B-FP8
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quantized_by: The Rock8
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---
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# Quacken-R1-14B-FP8
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### The Rock8 - Got any weights? 💪🦆
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| 30 |
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Native **fp8 E4M3** GGUF of **DeepSeek-R1-Distill-Qwen-14B** (a reasoning model) for
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**AMD RDNA4** (gfx1201 - Radeon AI PRO R9700 / RX 9070 / 9070 XT / W-series),
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quantized with **AMD Quark** from the full-precision BF16 weights by
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[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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(prefill) and `v_dot4_f32_fp8_fp8` (decode) - not a 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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- **Target:** AMD RDNA4 / gfx1201 (Radeon AI PRO R9700, RX 9070 / 9070 XT).
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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:** `DeepSeek-R1-Distill-Qwen-14B-Quark-F8E4M3.gguf` (16 GB).
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## Reasoning model - usage note
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This is an R1-distill reasoning model. It emits a chain-of-thought inside
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`<think>...</think>` before the final answer; llama.cpp / OpenAI-compatible servers
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surface that as `reasoning_content`. To **disable** thinking for a turn, append
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`/no_think` to the prompt (or set the chat template's thinking flag off). Expect
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longer generations by default because of the reasoning trace.
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## Source model + license
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- **Source:** [unsloth/DeepSeek-R1-Distill-Qwen-14B](https://huggingface.co/unsloth/DeepSeek-R1-Distill-Qwen-14B)
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(a mirror of deepseek-ai/DeepSeek-R1-Distill-Qwen-14B).
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- **License:** **MIT** (inherited from the source model; redistribution of this
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quantized derivative is permitted 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) | **8.97** |
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| Prefill `pp512` | **2499 t/s** |
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| Decode `tg128` | **33.4 t/s** |
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Benched on a single R9700 (gfx1201).
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## Run it
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### llama.cpp (The Rock8 fork)
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```bash
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# reasoning chat (keeps <think>)
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llama-cli -m DeepSeek-R1-Distill-Qwen-14B-Quark-F8E4M3.gguf -ngl 99 \
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-p "Solve step by step: a train travels 60 km in 40 minutes. What is its speed in km/h?"
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# fast, no reasoning trace
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llama-cli -m DeepSeek-R1-Distill-Qwen-14B-Quark-F8E4M3.gguf -ngl 99 -p "What do you call a dried grape? Answer in one word. /no_think"
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# bench
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llama-bench -m DeepSeek-R1-Distill-Qwen-14B-Quark-F8E4M3.gguf -ngl 99 -p 512 -n 128
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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-r1-14b:/models:ro \
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-e MODEL=/models/DeepSeek-R1-Distill-Qwen-14B-Quark-F8E4M3.gguf -e MODEL_NAME=Quacken-R1-14B-FP8 \
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-e HIP_VISIBLE_DEVICES=0 -p 13305:13305 \
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ghcr.io/the-monk/the-rock8:rdna4-tr713 serve
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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/Gorilla4X).
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- **Sibling model:**
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[Quacken-8B-FP8](https://huggingface.co/Gorilla4X/Quacken-8B-FP8).
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- **3 more coming:** Quacken-27B-FP8 (Qwen3.6-27B), Qwen3.6-35B-A3B (MoE) fp8, and Ornith-1.0-35B fp8 (in final validation).
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*Every artifact links to the others - land on any one, reach them all.*
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