Instructions to use OpenModel-Labs/Comet-1-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OpenModel-Labs/Comet-1-Preview with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="OpenModel-Labs/Comet-1-Preview", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("OpenModel-Labs/Comet-1-Preview", trust_remote_code=True, device_map="auto")

COMET

How to use OpenModel-Labs/Comet-1-Preview with COMET:

# No code snippets available yet for this library.

# To use this model, check the repository files and the library's documentation.

# Want to help? PRs adding snippets are welcome at:
# https://github.com/huggingface/huggingface.js

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use OpenModel-Labs/Comet-1-Preview with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OpenModel-Labs/Comet-1-Preview"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OpenModel-Labs/Comet-1-Preview",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/OpenModel-Labs/Comet-1-Preview

SGLang

How to use OpenModel-Labs/Comet-1-Preview 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 "OpenModel-Labs/Comet-1-Preview" \
    --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": "OpenModel-Labs/Comet-1-Preview",
		"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 "OpenModel-Labs/Comet-1-Preview" \
        --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": "OpenModel-Labs/Comet-1-Preview",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use OpenModel-Labs/Comet-1-Preview with Docker Model Runner:
```
docker model run hf.co/OpenModel-Labs/Comet-1-Preview
```

Comet-1-Preview / tokenizer_config.json

Bc-AI

Add Transformers support (modeling + config code), tokenizer/generation configs and model card

9df61c9 verified 1 day ago

Raw History Blame Contribute Delete

369 Bytes

{
  "tokenizer_class": "PreTrainedTokenizerFast",
  "bos_token": "<|endoftext|>",
  "eos_token": "<|endoftext|>",
  "unk_token": "<|endoftext|>",
  "pad_token": "<|padding|>",
  "add_prefix_space": false,
  "clean_up_tokenization_spaces": false,
  "model_input_names": [
    "input_ids",
    "attention_mask"
  ],
  "model_max_length": 8192,
  "padding_side": "left"
}

	{
	"tokenizer_class": "PreTrainedTokenizerFast",
	"bos_token": "<\|endoftext\|>",
	"eos_token": "<\|endoftext\|>",
	"unk_token": "<\|endoftext\|>",
	"pad_token": "<\|padding\|>",
	"add_prefix_space": false,
	"clean_up_tokenization_spaces": false,
	"model_input_names": [
	"input_ids",
	"attention_mask"
	],
	"model_max_length": 8192,
	"padding_side": "left"
	}