Instructions to use BEE-spoke-data/mega-ar-126m-4k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use BEE-spoke-data/mega-ar-126m-4k with Transformers:

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

pipe = pipeline("text-generation", model="BEE-spoke-data/mega-ar-126m-4k")

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("BEE-spoke-data/mega-ar-126m-4k", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use BEE-spoke-data/mega-ar-126m-4k with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "BEE-spoke-data/mega-ar-126m-4k"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BEE-spoke-data/mega-ar-126m-4k",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/BEE-spoke-data/mega-ar-126m-4k

SGLang

How to use BEE-spoke-data/mega-ar-126m-4k 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 "BEE-spoke-data/mega-ar-126m-4k" \
    --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": "BEE-spoke-data/mega-ar-126m-4k",
		"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 "BEE-spoke-data/mega-ar-126m-4k" \
        --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": "BEE-spoke-data/mega-ar-126m-4k",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use BEE-spoke-data/mega-ar-126m-4k with Docker Model Runner:
```
docker model run hf.co/BEE-spoke-data/mega-ar-126m-4k
```

pszemraj commited on 22 days ago

Commit

9302c82

verified ·

1 Parent(s): 5e88997

Update README.md

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Replace the detailed diagram with a modified image edited one

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@@ -80,10 +80,10 @@ For more info on MEGA (_& what some of the params above mean_), check out the [m
   />
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-_The more detailed and useful view is_
-![image](https://cdn-uploads.huggingface.co/production/uploads/60bccec062080d33f875cd0c/Fap2jlN62bnx0zXXP9kQ2.png)
 ## Usage

   />
 </a>
+A more detailed and useful view (_based on expanding the viewer + some reformatting_)
+![image](https://cdn-uploads.huggingface.co/production/uploads/60bccec062080d33f875cd0c/vyGuaB6134_jxQFDSEghw.png)
 ## Usage