Instructions to use SupraLabs/Supra-Mini-v4-2M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SupraLabs/Supra-Mini-v4-2M with Transformers:

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

pipe = pipeline("text-generation", model="SupraLabs/Supra-Mini-v4-2M")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("SupraLabs/Supra-Mini-v4-2M")
model = AutoModelForCausalLM.from_pretrained("SupraLabs/Supra-Mini-v4-2M")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use SupraLabs/Supra-Mini-v4-2M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SupraLabs/Supra-Mini-v4-2M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SupraLabs/Supra-Mini-v4-2M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/SupraLabs/Supra-Mini-v4-2M

SGLang

How to use SupraLabs/Supra-Mini-v4-2M 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 "SupraLabs/Supra-Mini-v4-2M" \
    --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": "SupraLabs/Supra-Mini-v4-2M",
		"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 "SupraLabs/Supra-Mini-v4-2M" \
        --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": "SupraLabs/Supra-Mini-v4-2M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use SupraLabs/Supra-Mini-v4-2M with Docker Model Runner:
```
docker model run hf.co/SupraLabs/Supra-Mini-v4-2M
```

LH-Tech-AI

Datdanboi25 commited on 7 days ago

Commit

06d9b0d

1 Parent(s): 74d1409

Update readme.md, fix vocab (8192 -> 4096) (#3)

Browse files

- Update readme.md, fix vocab (8192 -> 4096) (f6a7b5386b746a48a310a2287a82dea027d0b13b)

Co-authored-by: Dan P <Datdanboi25@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +1 -1

README.md CHANGED Viewed

@@ -25,7 +25,7 @@ Supra Mini **v4** 2M is a very tiny base model trained on **3 billion** tokens o
 - Parameters: 2,623,104 (2M)
 - Architecture: Llama
-- Vocab size with custom BPE tokenizer: 8192
 - Hidden Size: 128
 - Intermediate Size: 512
 - Hidden Layers: 6

 - Parameters: 2,623,104 (2M)
 - Architecture: Llama
+- Vocab size with custom BPE tokenizer: 4096
 - Hidden Size: 128
 - Intermediate Size: 512
 - Hidden Layers: 6