Instructions to use mondk/Greetings-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mondk/Greetings-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mondk/Greetings-model", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("mondk/Greetings-model", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use mondk/Greetings-model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mondk/Greetings-model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mondk/Greetings-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/mondk/Greetings-model
- SGLang
How to use mondk/Greetings-model 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 "mondk/Greetings-model" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mondk/Greetings-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "mondk/Greetings-model" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mondk/Greetings-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use mondk/Greetings-model with Docker Model Runner:
docker model run hf.co/mondk/Greetings-model
Download tokenizer.json from mondk/Greetings-model: direct link, hf CLI and curl.
- Browser
- Download file 1.93 kB
-
https://huggingface.co/mondk/Greetings-model/resolve/main/tokenizer.json
- Command line
-
hf download hf://mondk/Greetings-model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mondk/Greetings-model/resolve/main/tokenizer.json
1.93 kB
| { | |
| "version": "1.0", | |
| "truncation": null, | |
| "padding": null, | |
| "added_tokens": [ | |
| { | |
| "id": 0, | |
| "content": "<pad>", | |
| "single_word": false, | |
| "lstrip": false, | |
| "rstrip": false, | |
| "normalized": false, | |
| "special": true | |
| } | |
| ], | |
| "normalizer": { | |
| "type": "Lowercase" | |
| }, | |
| "pre_tokenizer": { | |
| "type": "Split", | |
| "pattern": { | |
| "Regex": "." | |
| }, | |
| "behavior": "Isolated", | |
| "invert": false | |
| }, | |
| "post_processor": null, | |
| "decoder": null, | |
| "model": { | |
| "type": "WordLevel", | |
| "vocab": { | |
| "\n": 1, | |
| " ": 2, | |
| "!": 3, | |
| "\"": 4, | |
| "#": 5, | |
| "%": 6, | |
| "'": 7, | |
| "(": 8, | |
| ")": 9, | |
| "*": 10, | |
| "+": 11, | |
| ",": 12, | |
| "-": 13, | |
| ".": 14, | |
| "/": 15, | |
| "0": 16, | |
| "1": 17, | |
| "2": 18, | |
| "3": 19, | |
| "4": 20, | |
| "5": 21, | |
| "6": 22, | |
| "7": 23, | |
| "8": 24, | |
| "9": 25, | |
| ":": 26, | |
| ";": 27, | |
| "<": 28, | |
| "=": 29, | |
| ">": 30, | |
| "?": 31, | |
| "A": 32, | |
| "B": 33, | |
| "C": 34, | |
| "D": 35, | |
| "E": 36, | |
| "F": 37, | |
| "G": 38, | |
| "H": 39, | |
| "I": 40, | |
| "J": 41, | |
| "K": 42, | |
| "L": 43, | |
| "M": 44, | |
| "N": 45, | |
| "O": 46, | |
| "P": 47, | |
| "Q": 48, | |
| "R": 49, | |
| "S": 50, | |
| "T": 51, | |
| "U": 52, | |
| "V": 53, | |
| "W": 54, | |
| "X": 55, | |
| "Y": 56, | |
| "Z": 57, | |
| "[": 58, | |
| "\\": 59, | |
| "]": 60, | |
| "_": 61, | |
| "a": 62, | |
| "b": 63, | |
| "c": 64, | |
| "d": 65, | |
| "e": 66, | |
| "f": 67, | |
| "g": 68, | |
| "h": 69, | |
| "i": 70, | |
| "j": 71, | |
| "k": 72, | |
| "l": 73, | |
| "m": 74, | |
| "n": 75, | |
| "o": 76, | |
| "p": 77, | |
| "q": 78, | |
| "r": 79, | |
| "s": 80, | |
| "t": 81, | |
| "u": 82, | |
| "v": 83, | |
| "w": 84, | |
| "x": 85, | |
| "y": 86, | |
| "z": 87, | |
| "{": 88, | |
| "}": 89, | |
| "<pad>": 0 | |
| }, | |
| "unk_token": "<pad>" | |
| } | |
| } |