Text Generation
Transformers
Safetensors
Indonesian
vegalm
causal-lm
indonesian
pretraining
knowledge-distillation
from-scratch
gqa
swiglu
hybrid-attention
custom_code
Instructions to use Veenn/vega-100m-indo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Veenn/vega-100m-indo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Veenn/vega-100m-indo", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Veenn/vega-100m-indo", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Veenn/vega-100m-indo with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Veenn/vega-100m-indo" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Veenn/vega-100m-indo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Veenn/vega-100m-indo
- SGLang
How to use Veenn/vega-100m-indo 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 "Veenn/vega-100m-indo" \ --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": "Veenn/vega-100m-indo", "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 "Veenn/vega-100m-indo" \ --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": "Veenn/vega-100m-indo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Veenn/vega-100m-indo with Docker Model Runner:
docker model run hf.co/Veenn/vega-100m-indo

- Xet hash:
- 90d45fa166523c7a159be2889cfb89869dea60937032c5134d8bec6ff2faced6
- Size of remote file:
- 117 kB
- SHA256:
- d5060e363f40c47afab3aa66e534f892c726d6a54887c1e2384a60f05849c0e7
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