Text Generation
Transformers
Safetensors
English
mistral
merged
qlora
unsloth
trl
sft
dpo
roleplay
creative-writing
chatml
conversational
text-generation-inference
Instructions to use zerolabllc/TeaAI-Nemo-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zerolabllc/TeaAI-Nemo-12B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zerolabllc/TeaAI-Nemo-12B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("zerolabllc/TeaAI-Nemo-12B") model = AutoModelForCausalLM.from_pretrained("zerolabllc/TeaAI-Nemo-12B", 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use zerolabllc/TeaAI-Nemo-12B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zerolabllc/TeaAI-Nemo-12B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zerolabllc/TeaAI-Nemo-12B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/zerolabllc/TeaAI-Nemo-12B
- SGLang
How to use zerolabllc/TeaAI-Nemo-12B 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 "zerolabllc/TeaAI-Nemo-12B" \ --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": "zerolabllc/TeaAI-Nemo-12B", "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 "zerolabllc/TeaAI-Nemo-12B" \ --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": "zerolabllc/TeaAI-Nemo-12B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Desktop
- Docker Model Runner
How to use zerolabllc/TeaAI-Nemo-12B with Docker Model Runner:
docker model run hf.co/zerolabllc/TeaAI-Nemo-12B
Download tokenizer_config.json from zerolabllc/TeaAI-Nemo-12B: direct link, hf CLI and curl.
- Browser
- Download file 659 Bytes
-
https://huggingface.co/zerolabllc/TeaAI-Nemo-12B/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://zerolabllc/TeaAI-Nemo-12B/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/zerolabllc/TeaAI-Nemo-12B/resolve/main/tokenizer_config.json
659 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "eos_token": "<|im_end|>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "unk_token": "<unk>", | |
| "chat_template": "{% for message in messages %}{% if message['role'] == 'user' %}{{'<|im_start|>user\n' + message['content'] + '<|im_end|>\n'}}{% elif message['role'] == 'assistant' %}{{'<|im_start|>assistant\n' + message['content'] + '<|im_end|>\n' }}{% else %}{{ '<|im_start|>system\n' + message['content'] + '<|im_end|>\n' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}" | |
| } |