Instructions to use djuna/G2-GSHT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djuna/G2-GSHT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="djuna/G2-GSHT") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("djuna/G2-GSHT") model = AutoModelForCausalLM.from_pretrained("djuna/G2-GSHT") 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 djuna/G2-GSHT with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "djuna/G2-GSHT" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "djuna/G2-GSHT", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/djuna/G2-GSHT
- SGLang
How to use djuna/G2-GSHT 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 "djuna/G2-GSHT" \ --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": "djuna/G2-GSHT", "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 "djuna/G2-GSHT" \ --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": "djuna/G2-GSHT", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use djuna/G2-GSHT with Docker Model Runner:
docker model run hf.co/djuna/G2-GSHT
chat template again?
{{ bos_token }}{% if messages | length > 0 %}{% if messages[0]['role'] == 'system' %}{{'user\n'}}{{ messages[0]['content'] | trim + '\n\n' }}{% if messages | length > 1 %}{{ messages[1]['content'] | trim }}{% elif messages | length > 1 %}{{ raise_exception('Error: Expected user role after system role.') }}{% endif %}{{'\n'}}{% for message in messages %}{% if loop.index > 2 %}{% if message['role'] == 'assistant' %}{{'model\n'}}{{ message['content'] | trim }}{{'\n'}}{% elif message['role'] == 'user' %}{{'user\n'}}{{ message['content'] | trim }}{{'\n'}}{% endif %}{% endif %}{% endfor %}{% else %}{% for message in messages %}{% if message['role'] == 'assistant' %}{{'model\n'}}{{ message['content'] | trim }}{{'\n'}}{% elif message['role'] == 'user' %}{{'user\n'}}{{ message['content'] | trim }}{{'\n'}}{% endif %}{% endfor %}{% endif %}{% endif %}{% if add_generation_prompt %}{{'model\n'}}{% endif %}
or this?
like ST mistal
{{ bos_token }}{% for message in messages %}{% if message['role'] == 'system' %}{{'user\n'+message['content'] | trim +'\nmodel\nUnderstood.\n'}}{% elif message['role'] == 'assistant' %}{{'model\n'+message['content'] | trim+'\n'}}{% elif message['role'] == 'user' %}{{'user\n'+message['content'] | trim+'\n'}}{% endif %}{% endfor %}{% if add_generation_prompt %}{{'model\n'}}{% endif %}