Text Generation
Transformers
Safetensors
PyTorch
English
rapnss
Rapnss
RA1
code
India
alpaca
custom_code
Instructions to use Rapnss/DevOps-Ultra-125M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rapnss/DevOps-Ultra-125M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Rapnss/DevOps-Ultra-125M", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Rapnss/DevOps-Ultra-125M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Rapnss/DevOps-Ultra-125M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Rapnss/DevOps-Ultra-125M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Rapnss/DevOps-Ultra-125M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Rapnss/DevOps-Ultra-125M
- SGLang
How to use Rapnss/DevOps-Ultra-125M 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 "Rapnss/DevOps-Ultra-125M" \ --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": "Rapnss/DevOps-Ultra-125M", "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 "Rapnss/DevOps-Ultra-125M" \ --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": "Rapnss/DevOps-Ultra-125M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Rapnss/DevOps-Ultra-125M with Docker Model Runner:
docker model run hf.co/Rapnss/DevOps-Ultra-125M
File size: 479 Bytes
62c9460 44498e1 62c9460 44498e1 62c9460 44498e1 0a72cae 44498e1 15e5fc7 62c9460 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"architectures": [
"RapnssForCausalLM"
],
"auto_map": {
"AutoConfig": "configuration_rapnss.RapnssConfig",
"AutoModelForCausalLM": "modeling_rapnss.RapnssForCausalLM"
},
"d_ff": 3072,
"d_model": 768,
"dropout": 0.1,
"dtype": "float32",
"is_decoder": true,
"max_seq_len": 512,
"model_type": "rapnss",
"n_heads": 12,
"n_layers": 12,
"num_hidden_layers": 12,
"transformers_version": "5.12.1",
"vocab_size": 50257
}
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