Instructions to use Irfanuruchi/Llama-2-13B-Computer-Engineering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Irfanuruchi/Llama-2-13B-Computer-Engineering with Transformers:

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

pipe = pipeline("text-generation", model="Irfanuruchi/Llama-2-13B-Computer-Engineering")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Irfanuruchi/Llama-2-13B-Computer-Engineering")
model = AutoModelForCausalLM.from_pretrained("Irfanuruchi/Llama-2-13B-Computer-Engineering", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Irfanuruchi/Llama-2-13B-Computer-Engineering with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Irfanuruchi/Llama-2-13B-Computer-Engineering"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Irfanuruchi/Llama-2-13B-Computer-Engineering",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Irfanuruchi/Llama-2-13B-Computer-Engineering

SGLang

How to use Irfanuruchi/Llama-2-13B-Computer-Engineering 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 "Irfanuruchi/Llama-2-13B-Computer-Engineering" \
    --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": "Irfanuruchi/Llama-2-13B-Computer-Engineering",
		"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 "Irfanuruchi/Llama-2-13B-Computer-Engineering" \
        --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": "Irfanuruchi/Llama-2-13B-Computer-Engineering",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Irfanuruchi/Llama-2-13B-Computer-Engineering with Docker Model Runner:
```
docker model run hf.co/Irfanuruchi/Llama-2-13B-Computer-Engineering
```

Irfanuruchi commited on Sep 24, 2025

Commit

74380f0

verified ·

1 Parent(s): 0a5aecd

Update README.md

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@@ -21,6 +21,12 @@ datasets:
 model_type: llama
 ---
 # Llama-2-13B-Computer-Engineering
 ### Overview

 model_type: llama
 ---
+[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-181717?style=for-the-badge&logo=github)](https://github.com/IrfanUruchi/Llama-2-13B-Computer-Engineering-)
+[![Model Weights](https://img.shields.io/badge/🤗-Model_Weights-FFD21F?style=for-the-badge)](https://huggingface.co/Irfanuruchi/Llama-2-13B-Computer-Engineering)
+[![Meta AI Llama 2 Licence](https://img.shields.io/badge/License-Apache_2.0-blue.svg?style=for-the-badge)](https://huggingface.co/meta-llama/Llama-2-13b-hf)
+---
 # Llama-2-13B-Computer-Engineering
 ### Overview