Instructions to use KaraKaraWarehouse/L3.1-70b-Inori with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use KaraKaraWarehouse/L3.1-70b-Inori with Transformers:

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

pipe = pipeline("text-generation", model="KaraKaraWarehouse/L3.1-70b-Inori")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("KaraKaraWarehouse/L3.1-70b-Inori")
model = AutoModelForCausalLM.from_pretrained("KaraKaraWarehouse/L3.1-70b-Inori", device_map="auto")
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 Settings

vLLM

How to use KaraKaraWarehouse/L3.1-70b-Inori with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "KaraKaraWarehouse/L3.1-70b-Inori"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "KaraKaraWarehouse/L3.1-70b-Inori",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/KaraKaraWarehouse/L3.1-70b-Inori

SGLang

How to use KaraKaraWarehouse/L3.1-70b-Inori 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 "KaraKaraWarehouse/L3.1-70b-Inori" \
    --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": "KaraKaraWarehouse/L3.1-70b-Inori",
		"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 "KaraKaraWarehouse/L3.1-70b-Inori" \
        --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": "KaraKaraWarehouse/L3.1-70b-Inori",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use KaraKaraWarehouse/L3.1-70b-Inori with Docker Model Runner:
```
docker model run hf.co/KaraKaraWarehouse/L3.1-70b-Inori
```

KaraKaraWitch commited on Aug 17, 2024

Commit

87a563c

verified ·

1 Parent(s): db6e6f8

Add files using upload-large-folder tool

Browse files

Files changed (1) hide show

mergekit_config.yml +15 -0

mergekit_config.yml ADDED Viewed

	@@ -0,0 +1,15 @@

+models:
+  - model: Fizzarolli/L3.1-70b-glitz-v0.2
+  - model: cyberagent/Llama-3.1-70B-Japanese-Instruct-2407
+  - model: Sao10K/L3-70B-Euryale-v2.1
+  - model: nothingiisreal/L3.1-70B-Celeste-V0.1-BF16
+  - model: sophosympatheia/New-Dawn-Llama-3.1-70B-v1.1
+  - model: gbueno86/Cathallama-70B
+  - model: abacusai/Dracarys-Llama-3.1-70B-Instruct
+merge_method: model_stock
+base_model: Fizzarolli/L3.1-70b-glitz-v0.2
+parameters:
+  normalize: true
+dtype: bfloat16