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

Libraries

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

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

pipe = pipeline("text-generation", model="shuyuej/Command-R-Plus-Smaller-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-Plus-Smaller-GPTQ")
model = AutoModelForCausalLM.from_pretrained("shuyuej/Command-R-Plus-Smaller-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-Plus-Smaller-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-Plus-Smaller-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-Plus-Smaller-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

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

SGLang

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

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

Command-R-Plus-Smaller-GPTQ / config.json

shuyuej

Update config.json

4d59903 verified almost 2 years ago

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	{
	"_name_or_path": "shuyuej/Command-R-Plus-Smaller-GPTQ",
	"architectures": [
	"CohereForCausalLM"
	],
	"attention_bias": false,
	"attention_dropout": 0.0,
	"bos_token_id": 5,
	"eos_token_id": 255001,
	"hidden_act": "silu",
	"hidden_size": 12288,
	"initializer_range": 0.02,
	"intermediate_size": 33792,
	"layer_norm_eps": 1e-05,
	"logit_scale": 0.8333333333333334,
	"max_position_embeddings": 8192,
	"model_max_length": 131072,
	"model_type": "cohere",
	"num_attention_heads": 96,
	"num_hidden_layers": 64,
	"num_key_value_heads": 8,
	"pad_token_id": 0,
	"quantization_config": {
	"batch_size": 1,
	"bits": 4,
	"block_name_to_quantize": null,
	"cache_block_outputs": true,
	"damp_percent": 0.1,
	"dataset": null,
	"desc_act": false,
	"exllama_config": {
	"version": 1
	},
	"group_size": 1024,
	"max_input_length": null,
	"model_seqlen": null,
	"module_name_preceding_first_block": null,
	"modules_in_block_to_quantize": null,
	"pad_token_id": null,
	"quant_method": "gptq",
	"sym": true,
	"tokenizer": null,
	"true_sequential": true,
	"use_cuda_fp16": false,
	"use_exllama": true
	},
	"rope_theta": 75000000.0,
	"torch_dtype": "float16",
	"transformers_version": "4.42.4",
	"use_cache": true,
	"use_qk_norm": true,
	"vocab_size": 256000
	}