Instructions to use mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit with MLX:

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

from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config

# Load the model
model, processor = load("mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit")
config = load_config("mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit")

# Prepare input
image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
prompt = "Describe this image."

# Apply chat template
formatted_prompt = apply_chat_template(
    processor, config, prompt, num_images=1
)

# Generate output
output = generate(model, processor, formatted_prompt, image)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit"

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": "mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit 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 "mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit"

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 mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit"

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 "mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit" \
  --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"

codelion commited on 11 days ago

Commit

c78c980

verified ·

1 Parent(s): ae21046

Astrea-R8-Chat-9B OptiQ mixed 4/8-bit quant

Browse files

Files changed (14) hide show

.gitattributes +1 -0
README.md +96 -0
chat_template.jinja +154 -0
config.json +2129 -0
generation_config.json +11 -0
model-00001-of-00002.safetensors +3 -0
model-00002-of-00002.safetensors +3 -0
model.safetensors.index.json +0 -0
optiq/metadata.json +1019 -0
optiq_vision.safetensors +3 -0
preprocessor_config.json +21 -0
tokenizer.json +3 -0
tokenizer_config.json +33 -0
video_preprocessor_config.json +21 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md ADDED Viewed

	@@ -0,0 +1,96 @@

+---
+license: apache-2.0
+library_name: mlx
+pipeline_tag: image-text-to-text
+base_model: HemmingwayAI/Astrea-R8-Chat-9B
+base_model_relation: quantized
+language:
+- en
+tags:
+- mlx
+- optiq
+- quantized
+- mixed-precision
+- 4bit
+- 8bit
+- qwen3.5
+- chat
+- creative-writing
+- vision-language-model
+- image-text-to-text
+- apple-silicon
+---
+# mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit
+> **Built with [mlx-optiq](https://mlx-optiq.com)**, the MLX-native toolkit to quantize, fine-tune, and serve LLMs locally on Apple Silicon, no PyTorch and no cloud. [Try the Lab](https://mlx-optiq.com/docs/lab/) · [All OptiQ quants](https://mlx-optiq.com/models) · [Docs](https://mlx-optiq.com/docs/)
+**Altworld's creative-writing model, quantized for a Mac.** A mixed-precision MLX quant of [HemmingwayAI/Astrea-R8-Chat-9B](https://huggingface.co/HemmingwayAI/Astrea-R8-Chat-9B), a Qwen3.5-9B fine-tune built for chat and fiction. 8.0 GB on disk, down from 18.8 GB bf16. See the [original card](https://huggingface.co/HemmingwayAI/Astrea-R8-Chat-9B) for what the model is trained to do and how Altworld evaluates it.
+OptiQ quantizes the language tower to mixed 4/8-bit and keeps the vision tower at bf16 in a sidecar, so one checkpoint does both text and images.
+## What it is
+| Property | Value |
+|---|---|
+| Base | HemmingwayAI/Astrea-R8-Chat-9B (Qwen3.5-9B fine-tune) |
+| Language tower | per-layer 4/8-bit: 116 layers at 4-bit, 134 at 8-bit (250 total) |
+| Vision tower | bf16, kept in `optiq_vision.safetensors` (333 tensors) |
+| On disk | 7.10 GB language + 0.91 GB vision |
+| Group size | 64 |
+| Context | 262,144 tokens |
+Following `llama.cpp`'s naming for mixed quants, the "4bit" label denotes the predominant precision, not the weighted average.
+## How the bit-widths were chosen
+The per-layer allocation was not measured on this model. It was transferred from [mlx-community/Qwen3.5-9B-OptiQ-4bit](https://huggingface.co/mlx-community/Qwen3.5-9B-OptiQ-4bit), whose allocation came from a KL-divergence sensitivity sweep over a [six-domain calibration mix](https://mlx-optiq.com/blog/calibration-mix). The two language towers share an architecture exactly, and all **250 tensors matched with none unmatched**.
+## Checked after conversion
+Run through this quant and its parent, Qwen3.5-9B-OptiQ-4bit, on Apple Silicon with greedy decoding and thinking off:
+| Prompt | Astrea | Parent |
+|---|---|---|
+| Capital of France, one word | Paris | Paris |
+| 120 km in 1.5 h, speed in km/h | 80 | 80 |
+| `is_palindrome(s)` ignoring case and non-letters | correct function | correct function |
+| What makes a good short-story opening, two sentences | coherent answer in its own wording | coherent answer |
+Image input: shown a red rectangle, a blue circle and the number 42, it answered "The image contains a red square, a blue circle, and the number 42 written in black."
+## Serve it with n-gram drafting
+Measured on a 24 GB M4, batch 1, greedy, median of three runs each:
+| Workload | Plain | `--ngram-draft 16` |
+|---|---|---|
+| Edit (rename a parameter across a file and return it) | 16.6 tok/s | **44.9 tok/s (2.7x)** |
+| Code generation | 16.7 tok/s | 18.0 tok/s (1.08x) |
+| Prose from a 1,024-token prompt | 16.6 tok/s | 16.2 tok/s (0.98x) |
+```bash
+pip install mlx-optiq
+optiq serve --model mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit --ngram-draft 16
+```
+This checkpoint has no MTP head, so `--mtp` does not apply.
+## Use it
+```bash
+# chat, images, and every app that talks to optiq serve
+optiq serve --model mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit --ngram-draft 16
+optiq lab --model mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit
+```
+Text only, with stock mlx-lm:
+```python
+from mlx_lm import load, generate
+model, tokenizer = load("mlx-community/Astrea-R8-Chat-9B-OptiQ-4bit")
+messages = [{"role": "user", "content": "Open a short story set on a night ferry."}]
+prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
+print(generate(model, tokenizer, prompt=prompt, max_tokens=400))
+```

chat_template.jinja ADDED Viewed

	@@ -0,0 +1,154 @@

+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- macro render_content(content, do_vision_count, is_system_content=false) %}
+    {%- if content is string %}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping %}
+        {%- for item in content %}
+            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain images.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set image_count.value = image_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Picture ' ~ image_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
+            {%- elif 'video' in item or item.type == 'video' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain videos.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set video_count.value = video_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Video ' ~ video_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
+            {%- elif 'text' in item %}
+                {{- item.text }}
+            {%- else %}
+                {{- raise_exception('Unexpected item type in content.') }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif content is none or content is undefined %}
+        {{- '' }}
+    {%- else %}
+        {{- raise_exception('Unexpected content type.') }}
+    {%- endif %}
+{%- endmacro %}
+{%- if not messages %}
+    {{- raise_exception('No messages provided.') }}
+{%- endif %}
+{%- if tools and tools is iterable and tools is not mapping %}
+    {{- '<|im_start|>system\n' }}
+    {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>" }}
+    {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- '\n\n' + content }}
+        {%- endif %}
+    {%- endif %}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" %}
+        {%- set content = render_content(message.content, false)|trim %}
+        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
+            {%- set ns.multi_step_tool = false %}
+            {%- set ns.last_query_index = index %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if ns.multi_step_tool %}
+    {{- raise_exception('No user query found in messages.') }}
+{%- endif %}
+{%- for message in messages %}
+    {%- set content = render_content(message.content, true)|trim %}
+    {%- if message.role == "system" %}
+        {%- if not loop.first %}
+            {{- raise_exception('System message must be at the beginning.') }}
+        {%- endif %}
+    {%- elif message.role == "user" %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content|trim %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if tool_call.function is defined %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {%- if loop.first %}
+                    {%- if content|trim %}
+                        {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- else %}
+                        {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- endif %}
+                {%- else %}
+                    {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                {%- endif %}
+                {%- if tool_call.arguments is defined %}
+                    {%- for args_name, args_value in tool_call.arguments|items %}
+                        {{- '<parameter=' + args_name + '>\n' }}
+                        {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
+                        {{- args_value }}
+                        {{- '\n</parameter>\n' }}
+                    {%- endfor %}
+                {%- endif %}
+                {{- '</function>\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.previtem and loop.previtem.role != "tool" %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if not loop.last and loop.nextitem.role != "tool" %}
+            {{- '<|im_end|>\n' }}
+        {%- elif loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- else %}
+        {{- raise_exception('Unexpected message role.') }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is not defined or enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- else %}
+        {{- '<think>\n' }}
+    {%- endif %}
+{%- endif %}

config.json ADDED Viewed

	@@ -0,0 +1,2129 @@

+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "dtype": "bfloat16",
+  "eos_token_id": [
+    248044,
+    248046
+  ],
+  "image_token_id": 248056,
+  "model_type": "qwen3_5",
+  "quantization": {
+    "group_size": 64,
+    "bits": 4,
+    "mode": "affine",
+    "language_model.model.embed_tokens": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.0.linear_attn.in_proj_qkv": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.0.linear_attn.in_proj_z": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.0.linear_attn.in_proj_b": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.0.linear_attn.in_proj_a": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.0.linear_attn.out_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.0.mlp.gate_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.0.mlp.down_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.0.mlp.up_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.1.linear_attn.in_proj_qkv": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.1.linear_attn.in_proj_z": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.1.linear_attn.in_proj_b": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.1.linear_attn.in_proj_a": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.1.linear_attn.out_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.1.mlp.gate_proj": {
+      "bits": 4,
+      "group_size": 64
+    },
+    "language_model.model.layers.1.mlp.down_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.1.mlp.up_proj": {
+      "bits": 4,
+      "group_size": 64
+    },
+    "language_model.model.layers.2.linear_attn.in_proj_qkv": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.2.linear_attn.in_proj_z": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.2.linear_attn.in_proj_b": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.2.linear_attn.in_proj_a": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.2.linear_attn.out_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.2.mlp.gate_proj": {
+      "bits": 4,
+      "group_size": 64
+    },
+    "language_model.model.layers.2.mlp.down_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.2.mlp.up_proj": {
+      "bits": 4,
+      "group_size": 64
+    },
+    "language_model.model.layers.3.self_attn.q_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.3.self_attn.k_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.3.self_attn.v_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.3.self_attn.o_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.3.mlp.gate_proj": {
+      "bits": 4,
+      "group_size": 64
+    },
+    "language_model.model.layers.3.mlp.down_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.3.mlp.up_proj": {
+      "bits": 4,
+      "group_size": 64
+    },
+    "language_model.model.layers.4.linear_attn.in_proj_qkv": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.4.linear_attn.in_proj_z": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.4.linear_attn.in_proj_b": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.4.linear_attn.in_proj_a": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.4.linear_attn.out_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.4.mlp.gate_proj": {
+      "bits": 4,
+      "group_size": 64
+    },
+    "language_model.model.layers.4.mlp.down_proj": {
+      "bits": 4,
+      "group_size": 64
+    },
+    "language_model.model.layers.4.mlp.up_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.5.linear_attn.in_proj_qkv": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.5.linear_attn.in_proj_z": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.5.linear_attn.in_proj_b": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.5.linear_attn.in_proj_a": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.5.linear_attn.out_proj": {
+      "bits": 8,
+      "group_size": 64
+    },
+    "language_model.model.layers.5.mlp.gate_proj": {
+      "bits": 4,
+      "group_size": 64
+    },
+    "language_model.model.layers.5.mlp.down_proj": {
+      "bits": 4,
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