Instructions to use ifable/gemma-2-Ifable-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ifable/gemma-2-Ifable-9B with Transformers:

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

pipe = pipeline("text-generation", model="ifable/gemma-2-Ifable-9B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ifable/gemma-2-Ifable-9B")
model = AutoModelForCausalLM.from_pretrained("ifable/gemma-2-Ifable-9B")
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 ifable/gemma-2-Ifable-9B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ifable/gemma-2-Ifable-9B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ifable/gemma-2-Ifable-9B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ifable/gemma-2-Ifable-9B

SGLang

How to use ifable/gemma-2-Ifable-9B 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 "ifable/gemma-2-Ifable-9B" \
    --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": "ifable/gemma-2-Ifable-9B",
		"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 "ifable/gemma-2-Ifable-9B" \
        --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": "ifable/gemma-2-Ifable-9B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ifable/gemma-2-Ifable-9B with Docker Model Runner:
```
docker model run hf.co/ifable/gemma-2-Ifable-9B
```

Thank you very much, this model is the best

by Anderson452 - opened Sep 18, 2024

Discussion

Anderson452

Sep 18, 2024

There is no other model who writes better than this one. He has excellent prose, And it generates coherent stories. I really congratulate you.

linzaiyun

ifable.ai org Sep 18, 2024

Thank you so much for the kind words. We are continually improving our model and we might release new models in the future with better writing qualities.

linzaiyun changed discussion status to closed Sep 19, 2024

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