Instructions to use shuyuej/Command-R-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use shuyuej/Command-R-GPTQ with Transformers:

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

pipe = pipeline("text-generation", model="shuyuej/Command-R-GPTQ")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("shuyuej/Command-R-GPTQ")
model = AutoModelForCausalLM.from_pretrained("shuyuej/Command-R-GPTQ")
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 shuyuej/Command-R-GPTQ with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/shuyuej/Command-R-GPTQ

SGLang

How to use shuyuej/Command-R-GPTQ 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 "shuyuej/Command-R-GPTQ" \
    --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": "shuyuej/Command-R-GPTQ",
		"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 "shuyuej/Command-R-GPTQ" \
        --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": "shuyuej/Command-R-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use shuyuej/Command-R-GPTQ with Docker Model Runner:
```
docker model run hf.co/shuyuej/Command-R-GPTQ
```

shuyuej commited on Jul 16, 2024

Commit

3f6058f

verified ·

1 Parent(s): 4f107d5

Upload folder using huggingface_hub

Browse files

Files changed (3) hide show

config.json +43 -0
gptq_model-4bit-128g.safetensors +3 -0
quantize_config.json +13 -0

config.json ADDED Viewed

	@@ -0,0 +1,43 @@

+{
+  "_name_or_path": "./save_folder",
+  "architectures": [
+    "CohereForCausalLM"
+  ],
+  "attention_bias": false,
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+  "model_type": "cohere",
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+  "num_hidden_layers": 40,
+  "num_key_value_heads": 64,
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+  "quantization_config": {
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+    "checkpoint_format": "gptq",
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+  "torch_dtype": "float16",
+  "transformers_version": "4.42.3",
+  "use_cache": true,
+  "use_qk_norm": false,
+  "vocab_size": 256000
+}

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quantize_config.json ADDED Viewed

	@@ -0,0 +1,13 @@

+{
+  "bits": 4,
+  "group_size": 128,
+  "damp_percent": 0.01,
+  "desc_act": true,
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+  "sym": true,
+  "true_sequential": true,
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+  "quant_method": "gptq",
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+}