Instructions to use SupraLabs/Supra-Mini-0.1M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SupraLabs/Supra-Mini-0.1M with Transformers:

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

pipe = pipeline("text-generation", model="SupraLabs/Supra-Mini-0.1M")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("SupraLabs/Supra-Mini-0.1M")
model = AutoModelForCausalLM.from_pretrained("SupraLabs/Supra-Mini-0.1M")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use SupraLabs/Supra-Mini-0.1M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SupraLabs/Supra-Mini-0.1M"
# 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-0.1M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/SupraLabs/Supra-Mini-0.1M

SGLang

How to use SupraLabs/Supra-Mini-0.1M 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-0.1M" \
    --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-0.1M",
		"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-0.1M" \
        --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-0.1M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use SupraLabs/Supra-Mini-0.1M with Docker Model Runner:
```
docker model run hf.co/SupraLabs/Supra-Mini-0.1M
```

LH-Tech-AI commited on 12 days ago

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@@ -19,7 +19,7 @@ tags:
 # 🦅 Supra Mini 0.1M
 Supra Mini 0.1M is a very tiny base model trained on 500 million tokens of Fineweb-Edu for 2 epochs to prove how well very tiny models can perform on world knowledge.
-# Model Config
 - Parameters: 117,648 (0.1M)
 - Architecture: Llama
@@ -32,25 +32,28 @@ Supra Mini 0.1M is a very tiny base model trained on 500 million tokens of Finew
 - Learning rate: 6e-4
 - Weight Decay: 0.01
 ## Benchmarks
 All benchmarks were executed using `lm-eval`.
-| Task          | Value        | Rating     |
-| :------------ | :----------: | ---------: |
-| Arc_Easy      | 0.2x         | RATING IN WORDS HERE |
-| Wikitext      | xx           | RATING IN WORDS HERE |
-| BLiMP         | 5x           | RATING IN WORDS HERE |
 ## Examples
-**Prompt:** PROMPT_HERE<br>
-**Output:**: OUTPUT_HERE
 <br><br>
-**Prompt:** PROMPT_HERE<br>
-**Output:**: OUTPUT_HERE
 <br><br>
-**Prompt:** PROMPT_HERE<br>
-**Output:**: OUTPUT_HERE
 ## Usage
 To use our model, just run this code using HF Transformers to execute the model:

 # 🦅 Supra Mini 0.1M
 Supra Mini 0.1M is a very tiny base model trained on 500 million tokens of Fineweb-Edu for 2 epochs to prove how well very tiny models can perform on world knowledge.
+## Model Config
 - Parameters: 117,648 (0.1M)
 - Architecture: Llama
 - Learning rate: 6e-4
 - Weight Decay: 0.01
+## Final Loss
+This model reached a final train loss after 2 epochs of **x.xxx**.
 ## Benchmarks
 All benchmarks were executed using `lm-eval`.
+| Task          | Value        | Random level |
+| :------------ | :----------: | -----------: |
+| Arc_Easy      | 0.2639       | 0.25 (25%)   |
+| Wikitext      | 25.1691      | -            |
+| BLiMP         | 0.5177       | 0.5 (50%)    |
 ## Examples
+**Prompt:** "Artificial intelligence is "<br>
+**Output:**: "Artificial intelligence is power by the leading the community, the book of the bring and in the made to the production of the back of an installing and consider in the several c"
 <br><br>
+**Prompt:** "The main concept of physics is "<br>
+**Output:**: "The main concept of physics is a struggle of the development of the company of the solution of the work of the first can be some of the supply a part of the state of the management,"
 <br><br>
+**Prompt:** "Once upon a time, "<br>
+**Output:**: "Once upon a time, so that he survey which is a self-described by the series of the surgery of the really a policy of the process of the southern of the material the stu"
 ## Usage
 To use our model, just run this code using HF Transformers to execute the model: