Instructions to use Thox-ai/ThoxUSB-Edge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Thox-ai/ThoxUSB-Edge 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 Thox-ai/ThoxUSB-Edge:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Thox-ai/ThoxUSB-Edge:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Thox-ai/ThoxUSB-Edge:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Thox-ai/ThoxUSB-Edge:Q4_K_M

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 Thox-ai/ThoxUSB-Edge:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Thox-ai/ThoxUSB-Edge:Q4_K_M

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 Thox-ai/ThoxUSB-Edge:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Thox-ai/ThoxUSB-Edge:Q4_K_M

Use Docker

docker model run hf.co/Thox-ai/ThoxUSB-Edge:Q4_K_M

LM Studio
Jan

vLLM

How to use Thox-ai/ThoxUSB-Edge with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Thox-ai/ThoxUSB-Edge"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Thox-ai/ThoxUSB-Edge",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Thox-ai/ThoxUSB-Edge:Q4_K_M

Ollama
How to use Thox-ai/ThoxUSB-Edge with Ollama:
```
ollama run hf.co/Thox-ai/ThoxUSB-Edge:Q4_K_M
```

Unsloth Studio

How to use Thox-ai/ThoxUSB-Edge 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 Thox-ai/ThoxUSB-Edge 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 Thox-ai/ThoxUSB-Edge to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Thox-ai/ThoxUSB-Edge to start chatting

How to use Thox-ai/ThoxUSB-Edge with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Thox-ai/ThoxUSB-Edge:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Thox-ai/ThoxUSB-Edge:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Thox-ai/ThoxUSB-Edge with Docker Model Runner:
```
docker model run hf.co/Thox-ai/ThoxUSB-Edge:Q4_K_M
```

Lemonade

How to use Thox-ai/ThoxUSB-Edge with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Thox-ai/ThoxUSB-Edge:Q4_K_M

Run and chat with the model

lemonade run user.ThoxUSB-Edge-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Thox-ai/ThoxUSB-Edge with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Thox-ai/ThoxUSB-Edge:Q4_K_M

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 Thox-ai/ThoxUSB-Edge:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Thox-ai/ThoxUSB-Edge with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Thox-ai/ThoxUSB-Edge:Q4_K_M

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 "Thox-ai/ThoxUSB-Edge:Q4_K_M" \
  --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"

tommytracx commited on 9 days ago

Commit

f4f876a

verified ·

1 Parent(s): 52cb9bc

Upload Qwen3_5ForCausalLM

Browse files

Files changed (4) hide show

README.md +8 -1
config.json +75 -0
generation_config.json +10 -0
model.safetensors +3 -0

README.md CHANGED Viewed

@@ -1,7 +1,14 @@
 ---
 license: apache-2.0
 base_model: Qwen/Qwen3.5-0.8B
-tags: [thox, on-device, edge, ThoxUSB, gguf]
 pipeline_tag: text-generation
 ---

 ---
 license: apache-2.0
 base_model: Qwen/Qwen3.5-0.8B
+tags:
+- thox
+- on-device
+- edge
+- ThoxUSB
+- gguf
+- trl
+- sft
 pipeline_tag: text-generation
 ---

config.json ADDED Viewed

	@@ -0,0 +1,75 @@

+{
+  "architectures": [
+    "Qwen3_5ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_output_gate": true,
+  "bos_token_id": null,
+  "dtype": "bfloat16",
+  "eos_token_id": 248046,
+  "full_attention_interval": 4,
+  "head_dim": 256,
+  "hidden_act": "silu",
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 3584,
+  "layer_types": [
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention"
+  ],
+  "linear_conv_kernel_dim": 4,
+  "linear_key_head_dim": 128,
+  "linear_num_key_heads": 16,
+  "linear_num_value_heads": 16,
+  "linear_value_head_dim": 128,
+  "mamba_ssm_dtype": "float32",
+  "max_position_embeddings": 262144,
+  "mlp_only_layers": [],
+  "model_type": "qwen3_5_text",
+  "mtp_num_hidden_layers": 1,
+  "mtp_use_dedicated_embeddings": false,
+  "num_attention_heads": 8,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 2,
+  "pad_token_id": 248044,
+  "partial_rotary_factor": 0.25,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "mrope_interleaved": true,
+    "mrope_section": [
+      11,
+      11,
+      10
+    ],
+    "partial_rotary_factor": 0.25,
+    "rope_theta": 10000000,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.15.0",
+  "use_cache": true,
+  "vocab_size": 248320
+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,10 @@

+{
+  "_from_model_config": true,
+  "eos_token_id": [
+    248046,
+    248044
+  ],
+  "pad_token_id": 248044,
+  "transformers_version": "5.15.0",
+  "use_cache": true
+}

model.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

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+size 1504827608