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673_trillion_parameters
Instructions to use ZeppelinCorp/Charm_15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZeppelinCorp/Charm_15 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ZeppelinCorp/Charm_15")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ZeppelinCorp/Charm_15") model = AutoModelForCausalLM.from_pretrained("ZeppelinCorp/Charm_15", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ZeppelinCorp/Charm_15 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ZeppelinCorp/Charm_15" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ZeppelinCorp/Charm_15", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ZeppelinCorp/Charm_15
- SGLang
How to use ZeppelinCorp/Charm_15 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 "ZeppelinCorp/Charm_15" \ --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": "ZeppelinCorp/Charm_15", "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 "ZeppelinCorp/Charm_15" \ --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": "ZeppelinCorp/Charm_15", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ZeppelinCorp/Charm_15 with Docker Model Runner:
docker model run hf.co/ZeppelinCorp/Charm_15
| { | |
| "version": "1.0", | |
| "model": "BPE", | |
| "vocab": { | |
| "<|begoftext|>": 0, | |
| "<|endoftext|>": 1, | |
| "<pad>": 2, | |
| "<unk>": 3, | |
| "the": 4, | |
| "a": 5, | |
| "and": 6, | |
| "to": 7, | |
| "of": 8, | |
| "in": 9, | |
| "I": 10, | |
| "is": 11, | |
| "it": 12, | |
| ".": 13, | |
| ",": 14, | |
| "th": 15, | |
| "an": 16, | |
| "ing": 17, | |
| "er": 18, | |
| "on": 19 | |
| }, | |
| "merges": [ | |
| "t h", | |
| "th e", | |
| "a n", | |
| "a nd", | |
| "i n", | |
| "o f", | |
| "to k", | |
| "i s", | |
| "in g", | |
| "e r", | |
| "o n" | |
| ], | |
| "special_tokens": { | |
| "pad_token": "<pad>", | |
| "bos_token": "<|begoftext|>", | |
| "eos_token": "<|endoftext|>", | |
| "unk_token": "<unk>" | |
| } | |
| } |