Instructions to use IMvision12/lamoe-247 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IMvision12/lamoe-247 with Transformers:

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

pipe = pipeline("text-generation", model="IMvision12/lamoe-247")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("IMvision12/lamoe-247", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use IMvision12/lamoe-247 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IMvision12/lamoe-247"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IMvision12/lamoe-247",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/IMvision12/lamoe-247

SGLang

How to use IMvision12/lamoe-247 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 "IMvision12/lamoe-247" \
    --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": "IMvision12/lamoe-247",
		"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 "IMvision12/lamoe-247" \
        --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": "IMvision12/lamoe-247",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use IMvision12/lamoe-247 with Docker Model Runner:
```
docker model run hf.co/IMvision12/lamoe-247
```

lamoe-247 / tokenizer_config.json

IMvision12

Add Transformers AutoModel compatibility with unchanged trained weights

ced76af verified 17 days ago

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464 Bytes

{
  "backend": "tokenizers",
  "bos_token": "<|bos|>",
  "clean_up_tokenization_spaces": false,
  "eos_token": "<|eos|>",
  "extra_special_tokens": [
    "<|fim_prefix|>",
    "<|fim_suffix|>",
    "<|fim_middle|>",
    "<|system|>",
    "<|user|>",
    "<|assistant|>",
    "<|end_turn|>"
  ],
  "model_max_length": 2048,
  "pad_token": "<|pad|>",
  "padding_side": "left",
  "tokenizer_class": "TokenizersBackend",
  "unk_token": "<|unk|>"
}

	{
	"backend": "tokenizers",
	"bos_token": "<\|bos\|>",
	"clean_up_tokenization_spaces": false,
	"eos_token": "<\|eos\|>",
	"extra_special_tokens": [
	"<\|fim_prefix\|>",
	"<\|fim_suffix\|>",
	"<\|fim_middle\|>",
	"<\|system\|>",
	"<\|user\|>",
	"<\|assistant\|>",
	"<\|end_turn\|>"
	],
	"model_max_length": 2048,
	"pad_token": "<\|pad\|>",
	"padding_side": "left",
	"tokenizer_class": "TokenizersBackend",
	"unk_token": "<\|unk\|>"
	}