Instructions to use maywell/Synatra_TbST11B_EP01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use maywell/Synatra_TbST11B_EP01 with Transformers:

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

pipe = pipeline("text-generation", model="maywell/Synatra_TbST11B_EP01")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("maywell/Synatra_TbST11B_EP01")
model = AutoModelForCausalLM.from_pretrained("maywell/Synatra_TbST11B_EP01", 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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use maywell/Synatra_TbST11B_EP01 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "maywell/Synatra_TbST11B_EP01"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "maywell/Synatra_TbST11B_EP01",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/maywell/Synatra_TbST11B_EP01

SGLang

How to use maywell/Synatra_TbST11B_EP01 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 "maywell/Synatra_TbST11B_EP01" \
    --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": "maywell/Synatra_TbST11B_EP01",
		"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 "maywell/Synatra_TbST11B_EP01" \
        --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": "maywell/Synatra_TbST11B_EP01",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use maywell/Synatra_TbST11B_EP01 with Docker Model Runner:
```
docker model run hf.co/maywell/Synatra_TbST11B_EP01
```

Synatra_TbST11B_EP01

Made by StableFluffy

Contact (Do not Contact for personal things.) Discord : is.maywell Telegram : AlzarTakkarsen

License

This model is strictly non-commercial (cc-by-nc-4.0) use only which takes priority over the MISTRAL APACHE 2.0. The "Model" is completely free (ie. base model, derivates, merges/mixes) to use for non-commercial purposes as long as the the included cc-by-nc-4.0 license in any parent repository, and the non-commercial use statute remains, regardless of other models' licences. The licence can be changed after new model released. If you are to use this model for commercial purpose, Contact me.

Model Details

Base Model
mistralai/Mistral-7B-Instruct-v0.1

Trained On
A100 80GB * 4

Model Benchmark


> Readme format: [beomi/llama-2-ko-7b](https://huggingface.co/beomi/llama-2-ko-7b)

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Synatra_TbST11B_EP01

Synatra_TbST11B_EP01

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Model Benchmark

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