Instructions to use Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw with Transformers:

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

pipe = pipeline("text-generation", model="Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw")
model = AutoModelForCausalLM.from_pretrained("Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw")
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 Settings

vLLM

How to use Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw

SGLang

How to use Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw 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 "Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw" \
    --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": "Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw",
		"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 "Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw" \
        --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": "Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw with Docker Model Runner:
```
docker model run hf.co/Downtown-Case/Star-Command-R-Lite-32B-v1-exl2-4bpw
```

Downtown-Case commited on Sep 19, 2024

Commit

47e54d8

verified ·

1 Parent(s): 142362d

Update README.md

Browse files

Files changed (1) hide show

README.md +5 -3

README.md CHANGED Viewed

@@ -1,10 +1,12 @@
 ---
-base_model: [CohereForAI/c4ai-command-r-08-2024, TheDrummer/Star-Command-R-32B-v1]
 library_name: transformers
 tags:
 - mergekit
 - merge
 ---
 # Star-Command-R-Lite-32B-v1
@@ -42,4 +44,4 @@ parameters:
     - value: 0.5
 base_model: CohereForAI/c4ai-command-r-08-2024
 dtype: bfloat16
-```

 ---
+base_model:
+- CohereForAI/c4ai-command-r-08-2024
+- TheDrummer/Star-Command-R-32B-v1
+- Downtown-Case/Star-Command-R-Lite-32B-v1
 library_name: transformers
 tags:
 - mergekit
 - merge
 ---
 # Star-Command-R-Lite-32B-v1
     - value: 0.5
 base_model: CohereForAI/c4ai-command-r-08-2024
 dtype: bfloat16
+```