Instructions to use poedator/opt-125m-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use poedator/opt-125m-bnb-4bit with Transformers:

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

pipe = pipeline("text-generation", model="poedator/opt-125m-bnb-4bit")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("poedator/opt-125m-bnb-4bit")
model = AutoModelForCausalLM.from_pretrained("poedator/opt-125m-bnb-4bit")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use poedator/opt-125m-bnb-4bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "poedator/opt-125m-bnb-4bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "poedator/opt-125m-bnb-4bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/poedator/opt-125m-bnb-4bit

SGLang

How to use poedator/opt-125m-bnb-4bit 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 "poedator/opt-125m-bnb-4bit" \
    --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": "poedator/opt-125m-bnb-4bit",
		"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 "poedator/opt-125m-bnb-4bit" \
        --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": "poedator/opt-125m-bnb-4bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use poedator/opt-125m-bnb-4bit with Docker Model Runner:
```
docker model run hf.co/poedator/opt-125m-bnb-4bit
```

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Check out the documentation for more information.

facebook/OPT-125m quantized using bitsandbytes 4-bit NF4 quantization. All license matters are set based on the underlying facebook/OPT-125m model.

This model is work in progress, use it for testing https://github.com/huggingface/transformers/pull/26037 pull request only.

known issue: safetensors deleted linked "quant_map" / "nested_quant_map" items.

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Safetensors

Model size

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Tensor type

F32

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