Instructions to use DJLougen/Ornstein3.6-35B-A3B-RYS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DJLougen/Ornstein3.6-35B-A3B-RYS with Transformers:

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

pipe = pipeline("text-generation", model="DJLougen/Ornstein3.6-35B-A3B-RYS")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DJLougen/Ornstein3.6-35B-A3B-RYS")
model = AutoModelForCausalLM.from_pretrained("DJLougen/Ornstein3.6-35B-A3B-RYS")
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 DJLougen/Ornstein3.6-35B-A3B-RYS with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DJLougen/Ornstein3.6-35B-A3B-RYS"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DJLougen/Ornstein3.6-35B-A3B-RYS",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DJLougen/Ornstein3.6-35B-A3B-RYS

SGLang

How to use DJLougen/Ornstein3.6-35B-A3B-RYS 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 "DJLougen/Ornstein3.6-35B-A3B-RYS" \
    --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": "DJLougen/Ornstein3.6-35B-A3B-RYS",
		"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 "DJLougen/Ornstein3.6-35B-A3B-RYS" \
        --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": "DJLougen/Ornstein3.6-35B-A3B-RYS",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use DJLougen/Ornstein3.6-35B-A3B-RYS with Docker Model Runner:
```
docker model run hf.co/DJLougen/Ornstein3.6-35B-A3B-RYS
```

Ornstein3.5-397B?

by willfalco - opened 24 days ago

Discussion

willfalco

24 days ago

397B model has so much knowledge, but so lazy to use it, like it is resisting common sense
maybe RYS will make it great .. again :)

thank you for your great models!

willfalco changed discussion title from Qwopus3.5-397B? to Ornstein3.5-397B? 24 days ago

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