Text Generation
Transformers
Safetensors
Italian
gpt2
DAC
data-ai
DATA-AI
transformer
experimental
text-generation-inference
Instructions to use Mattimax/microDAC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mattimax/microDAC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Mattimax/microDAC")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Mattimax/microDAC") model = AutoModelForCausalLM.from_pretrained("Mattimax/microDAC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Mattimax/microDAC with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Mattimax/microDAC" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mattimax/microDAC", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Mattimax/microDAC
- SGLang
How to use Mattimax/microDAC 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 "Mattimax/microDAC" \ --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": "Mattimax/microDAC", "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 "Mattimax/microDAC" \ --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": "Mattimax/microDAC", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Mattimax/microDAC with Docker Model Runner:
docker model run hf.co/Mattimax/microDAC
Download checkpoint-1308/optimizer.pt from Mattimax/microDAC: direct link, hf CLI and curl.
- Browser
- Download file 543 MB
-
https://huggingface.co/Mattimax/microDAC/resolve/main/checkpoint-1308/optimizer.pt
- Command line
-
hf download hf://Mattimax/microDAC/checkpoint-1308/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Mattimax/microDAC/resolve/main/checkpoint-1308/optimizer.pt
543 MB
- Xet hash:
- efcab29bcfbeb3bd3f1c308f6a63318fa7bdd6a3c061a77dd1dae2a9c9862454
- Size of remote file:
- 543 MB
- SHA256:
- 56b1993e5ba37c1901e791e688885a36c988f01cd3bfde6e9568c7b262f8d1ac
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