Instructions to use WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit"

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 WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit"

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 "WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

WaveCut commited on Jul 13

Commit

96a21c6

verified ·

1 Parent(s): f0bcd17

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@@ -1,39 +1,66 @@
 ---
 license: apache-2.0
-base_model: WaveCut/Qwythos-9B-v2-Heretic
 tags:
-- heretic
-- uncensored
-- abliteration
-- mlx
 pipeline_tag: text-generation
-library_name: mlx
 ---
-# WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit
-This model [WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit](https://huggingface.co/WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit) was
-converted to MLX format from [WaveCut/Qwythos-9B-v2-Heretic](https://huggingface.co/WaveCut/Qwythos-9B-v2-Heretic)
-using mlx-lm version **0.31.3**.
-## Use with mlx
 ```bash
-pip install mlx-lm
 ```
 ```python
 from mlx_lm import load, generate
 model, tokenizer = load("WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit")
-prompt = "hello"
-if tokenizer.chat_template is not None:
-    messages = [{"role": "user", "content": prompt}]
-    prompt = tokenizer.apply_chat_template(
-        messages, add_generation_prompt=True, return_dict=False,
-    )
-response = generate(model, tokenizer, prompt=prompt, verbose=True)
-```

 ---
+language:
+  - en
+  - ru
 license: apache-2.0
+library_name: mlx
+base_model:
+  - WaveCut/Qwythos-9B-v2-Heretic
+base_model_relation: quantized
 tags:
+  - heretic
+  - uncensored
+  - abliteration
+  - mlx
+  - apple-silicon
+  - qwen3.5
 pipeline_tag: text-generation
 ---
+# Qwythos-9B-v2-Heretic-MLX-8bit
+**MLX 8-bit quantization** of [`WaveCut/Qwythos-9B-v2-Heretic`](https://huggingface.co/WaveCut/Qwythos-9B-v2-Heretic) — the Heretic-decensored version of [`empero-ai/Qwythos-9B-v2`](https://huggingface.co/empero-ai/Qwythos-9B-v2). Built for **Apple Silicon** (M1/M2/M3/M4).
+## Specs
+| Field | Value |
+|---|---|
+| Bits/weight | **8.501** |
+| File size | ~9.5 GB |
+| Minimum RAM | ~11 GB unified memory |
+## Quantization
+| Step | Tool | Version |
+|---|---|---|
+| Convert + quantize | `mlx_lm.convert` | **mlx-lm 0.31.3** (mlx 0.31.x) |
+| Quant mode | `affine` (default) | `-q --q-bits 8` |
 ```bash
+python -m mlx_lm.convert \
+  --hf-path WaveCut/Qwythos-9B-v2-Heretic \
+  -q --q-bits 8 \
+  --upload-repo WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit
 ```
+## Usage
 ```python
 from mlx_lm import load, generate
 model, tokenizer = load("WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit")
+response = generate(model, tokenizer, prompt="Hello", max_tokens=256)
+print(response)
+```
+```bash
+# CLI
+mlx_lm.generate --model WaveCut/Qwythos-9B-v2-Heretic-MLX-8bit --prompt "Hello"
+```
+## Architecture
+Qwen3.5 **hybrid** — 32 blocks mixing attention and SSM (Mamba-style) layers. Supported in mlx-lm ≥ 0.31.0.
+## Disclaimer
+Uncensored (safety alignment removed via Heretic). The original `empero-ai/Qwythos-9B-v2` maintainers are not affiliated with this derivative. Use responsibly.