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 commited on 6 days ago

Commit

274c8f4

verified ·

1 Parent(s): bf1bea9

Update config.json

Browse files

Files changed (1) hide show

config.json +9 -9

config.json CHANGED Viewed

@@ -7,26 +7,26 @@
   "bos_token_id": 0,
   "dtype": "float32",
   "eos_token_id": 2,
-  "head_dim": 8,
   "hidden_act": "silu",
-  "hidden_size": 64,
   "initializer_range": 0.02,
-  "intermediate_size": 128,
   "max_position_embeddings": 512,
   "mlp_bias": false,
   "model_type": "llama",
-  "num_attention_heads": 8,
-  "num_hidden_layers": 5,
-  "num_key_value_heads": 8,
   "pad_token_id": 1,
   "pretraining_tp": 1,
   "rms_norm_eps": 1e-06,
   "rope_parameters": {
-    "rope_theta": 10000.0,
     "rope_type": "default"
   },
   "tie_word_embeddings": true,
   "transformers_version": "5.8.1",
   "use_cache": false,
-  "vocab_size": 4096
-}

   "bos_token_id": 0,
   "dtype": "float32",
   "eos_token_id": 2,
+  "head_dim": 32,
   "hidden_act": "silu",
+  "hidden_size": 128,
   "initializer_range": 0.02,
+  "intermediate_size": 512,
   "max_position_embeddings": 512,
   "mlp_bias": false,
   "model_type": "llama",
+  "num_attention_heads": 4,
+  "num_hidden_layers": 6,
+  "num_key_value_heads": 4,
   "pad_token_id": 1,
   "pretraining_tp": 1,
   "rms_norm_eps": 1e-06,
   "rope_parameters": {
+    "rope_theta": 500000,
     "rope_type": "default"
   },
   "tie_word_embeddings": true,
   "transformers_version": "5.8.1",
   "use_cache": false,
+  "vocab_size": 8192
+}