Instructions to use royleibov/granite-7b-instruct-ZipNN-Compressed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use royleibov/granite-7b-instruct-ZipNN-Compressed with Transformers:

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

pipe = pipeline("text-generation", model="royleibov/granite-7b-instruct-ZipNN-Compressed")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("royleibov/granite-7b-instruct-ZipNN-Compressed")
model = AutoModelForCausalLM.from_pretrained("royleibov/granite-7b-instruct-ZipNN-Compressed")
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 royleibov/granite-7b-instruct-ZipNN-Compressed with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "royleibov/granite-7b-instruct-ZipNN-Compressed"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "royleibov/granite-7b-instruct-ZipNN-Compressed",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/royleibov/granite-7b-instruct-ZipNN-Compressed

SGLang

How to use royleibov/granite-7b-instruct-ZipNN-Compressed 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 "royleibov/granite-7b-instruct-ZipNN-Compressed" \
    --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": "royleibov/granite-7b-instruct-ZipNN-Compressed",
		"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 "royleibov/granite-7b-instruct-ZipNN-Compressed" \
        --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": "royleibov/granite-7b-instruct-ZipNN-Compressed",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use royleibov/granite-7b-instruct-ZipNN-Compressed with Docker Model Runner:
```
docker model run hf.co/royleibov/granite-7b-instruct-ZipNN-Compressed
```

granite-7b-instruct-ZipNN-Compressed

Commit History

Add ZipNN text

7033f8d
verified

royleibov commited on Sep 15, 2024

Add use this model

ddd9df0
verified

royleibov commited on Sep 15, 2024

Add support for transformers library

a2767ea
verified

royleibov commited on Sep 15, 2024

Add bold

999e3ca
verified

royleibov commited on Sep 15, 2024

Fix zipnn_hf

a9f9d09
verified

royleibov commited on Sep 15, 2024

Clarify this is a clone and correct the use of ZipNN

2e0bd6e
verified

royleibov commited on Sep 12, 2024

Add scripts

5c653a0

royleibov commited on Sep 9, 2024

delete scripts

51d629d

royleibov commited on Sep 9, 2024