Instructions to use mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ")
model = AutoModelForCausalLM.from_pretrained("mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ

SGLang

How to use mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ with Docker Model Runner:
```
docker model run hf.co/mattbucci/Qwen3-Coder-30B-A3B-REAP-AWQ
```

mattbucci commited on 26 days ago

Commit

ef047d6

verified ·

1 Parent(s): 0c43e46

add config.json

Browse files

Files changed (1) hide show

config.json +75 -0

config.json ADDED Viewed

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

+{
+  "architectures": [
+    "Qwen3MoeForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "decoder_sparse_step": 1,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 6144,
+  "max_position_embeddings": 262144,
+  "max_window_layers": 48,
+  "merge_args": {
+    "batch_size": 2,
+    "cache_dir": null,
+    "calibration_data_size": 1024,
+    "checkpoint_dir": null,
+    "checkpoint_every": 1,
+    "dataset": "c4+math+code",
+    "download": false,
+    "group_size": 16,
+    "grouping": "ream",
+    "merge_size": 96,
+    "merging": "none",
+    "mix_ratio": "0.0,0.3,0.7",
+    "model": "/home/letsrtfm/AI/models/Qwen3-Coder-30B-A3B-BF16",
+    "mtp_safe_tensors": null,
+    "no_gate_output": false,
+    "no_gated_sim": false,
+    "no_sequential": false,
+    "resume_from": null,
+    "saliency": "reap",
+    "save_path": "/home/letsrtfm/AI/models/Qwen3-Coder-30B-A3B-REAP-BF16"
+  },
+  "mlp_only_layers": [],
+  "model_type": "qwen3_moe",
+  "moe_intermediate_size": 768,
+  "norm_topk_prob": true,
+  "num_attention_heads": 32,
+  "num_experts_per_tok": 8,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 4,
+  "num_local_experts": 96,
+  "output_router_logits": false,
+  "pad_token_id": null,
+  "quantization_config": {
+    "bits": 4,
+    "group_size": 128,
+    "quant_method": "awq",
+    "version": "gemm",
+    "zero_point": true,
+    "modules_to_not_convert": [],
+    "ignore": [
+      "lm_head",
+      "re:.*mlp\\.gate$"
+    ]
+  },
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 10000000,
+    "rope_type": "default"
+  },
+  "router_aux_loss_coef": 0.001,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "5.5.4",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}