Instructions to use RAANA-IA/Kira with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RAANA-IA/Kira with Transformers:

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

pipe = pipeline("text-generation", model="RAANA-IA/Kira")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("RAANA-IA/Kira")
model = AutoModelForCausalLM.from_pretrained("RAANA-IA/Kira")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use RAANA-IA/Kira with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/RAANA-IA/Kira

SGLang

How to use RAANA-IA/Kira 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 "RAANA-IA/Kira" \
    --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": "RAANA-IA/Kira",
		"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 "RAANA-IA/Kira" \
        --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": "RAANA-IA/Kira",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use RAANA-IA/Kira with Docker Model Runner:
```
docker model run hf.co/RAANA-IA/Kira
```

Exemples de génération

by Clemylia - opened Jan 25

Discussion

Clemylia

RaAna org Jan 25

Je rita lola, momorita sallia, aska aze rosa.
Kiara rita lola, momorita sallia, aska aze lola.
Rita lola, momorita sallia, ja aze rosa.
Rita lola, momorita sallia, rita lola.

Mona rita, momorita sallia, aska aze rosa.
Je parle le rita, rita lola, momorita sallia.
Fenus rita, lola kina, momorita sallia.
Aze rosa, rita lola, momorita sallia.
Je parle le aze, rita lola, momorita sallia.
Fenus aze, lola kina, momorita sallia.

Mona with a couplet, rita lola with a refrain, momorita sallia.
Ja aze Rosa, rita Lola, momorita sallia.
Asnina Erie Kiara, momorita Salli, ja aze Rosa.

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