Text Generation
PEFT
Safetensors
Transformers
English
network-engineering
network-operations
cloud-operations
network-troubleshooting
network-automation
cisco
palo-alto-networks
fortinet
juniper
aws
azure
gcp
bgp
ospf
lora
sft
trl
conversational
Instructions to use Reponx/Network-Cloud-Ops-Engineer-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Reponx/Network-Cloud-Ops-Engineer-9B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-9B") model = PeftModel.from_pretrained(base_model, "Reponx/Network-Cloud-Ops-Engineer-9B") - Transformers
How to use Reponx/Network-Cloud-Ops-Engineer-9B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Reponx/Network-Cloud-Ops-Engineer-9B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Reponx/Network-Cloud-Ops-Engineer-9B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Reponx/Network-Cloud-Ops-Engineer-9B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Reponx/Network-Cloud-Ops-Engineer-9B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Reponx/Network-Cloud-Ops-Engineer-9B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Reponx/Network-Cloud-Ops-Engineer-9B
- SGLang
How to use Reponx/Network-Cloud-Ops-Engineer-9B 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 "Reponx/Network-Cloud-Ops-Engineer-9B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Reponx/Network-Cloud-Ops-Engineer-9B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "Reponx/Network-Cloud-Ops-Engineer-9B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Reponx/Network-Cloud-Ops-Engineer-9B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Reponx/Network-Cloud-Ops-Engineer-9B with Docker Model Runner:
docker model run hf.co/Reponx/Network-Cloud-Ops-Engineer-9B
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## License
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Apache-2.0
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## License
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Apache-2.0
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> **⚠️ Newer version available:** This Qwen-based model is replaced by
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> [Reponx/Llama-3.1-8B-Reponx-Network-Cloud-Ops](https://huggingface.co/Reponx/Llama-3.1-8B-Reponx-Network-Cloud-Ops),
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> which covers Cisco, Palo Alto Networks, Azure and AWS and is trained to use retrieved reference documents.
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> This repository is kept for existing users.
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