Instructions to use ReallyNotMe/model16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ReallyNotMe/model16bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ReallyNotMe/model16bit") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ReallyNotMe/model16bit") model = AutoModelForCausalLM.from_pretrained("ReallyNotMe/model16bit") 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 ReallyNotMe/model16bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ReallyNotMe/model16bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ReallyNotMe/model16bit", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ReallyNotMe/model16bit
- SGLang
How to use ReallyNotMe/model16bit 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 "ReallyNotMe/model16bit" \ --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": "ReallyNotMe/model16bit", "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 "ReallyNotMe/model16bit" \ --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": "ReallyNotMe/model16bit", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Studio
How to use ReallyNotMe/model16bit with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ReallyNotMe/model16bit to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ReallyNotMe/model16bit to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ReallyNotMe/model16bit to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="ReallyNotMe/model16bit", max_seq_length=2048, ) - Docker Model Runner
How to use ReallyNotMe/model16bit with Docker Model Runner:
docker model run hf.co/ReallyNotMe/model16bit
| { | |
| "</tool_call>": 145124, | |
| "<tool_call>": 145123, | |
| "<|box_end|>": 145115, | |
| "<|box_start|>": 145114, | |
| "<|endoftext|>": 145109, | |
| "<|file_sep|>": 145130, | |
| "<|fim_middle|>": 145126, | |
| "<|fim_pad|>": 145128, | |
| "<|fim_prefix|>": 145125, | |
| "<|fim_suffix|>": 145127, | |
| "<|free_token10|>": 145140, | |
| "<|free_token11|>": 145141, | |
| "<|free_token12|>": 145142, | |
| "<|free_token13|>": 145143, | |
| "<|free_token14|>": 145144, | |
| "<|free_token15|>": 145145, | |
| "<|free_token16|>": 145146, | |
| "<|free_token17|>": 145147, | |
| "<|free_token18|>": 145148, | |
| "<|free_token19|>": 145149, | |
| "<|free_token1|>": 145131, | |
| "<|free_token20|>": 145150, | |
| "<|free_token21|>": 145151, | |
| "<|free_token2|>": 145132, | |
| "<|free_token3|>": 145133, | |
| "<|free_token4|>": 145134, | |
| "<|free_token5|>": 145135, | |
| "<|free_token6|>": 145136, | |
| "<|free_token7|>": 145137, | |
| "<|free_token8|>": 145138, | |
| "<|free_token9|>": 145139, | |
| "<|im_end|>": 145111, | |
| "<|im_start|>": 145110, | |
| "<|image_pad|>": 145121, | |
| "<|object_ref_end|>": 145113, | |
| "<|object_ref_start|>": 145112, | |
| "<|quad_end|>": 145117, | |
| "<|quad_start|>": 145116, | |
| "<|repo_name|>": 145129, | |
| "<|video_pad|>": 145122, | |
| "<|vision_end|>": 145119, | |
| "<|vision_pad|>": 145120, | |
| "<|vision_start|>": 145118 | |
| } | |