Instructions to use georgesung/llama2_7b_openorca_35k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use georgesung/llama2_7b_openorca_35k with Transformers:

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

pipe = pipeline("text-generation", model="georgesung/llama2_7b_openorca_35k", device_map="auto")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("georgesung/llama2_7b_openorca_35k")
model = AutoModelForCausalLM.from_pretrained("georgesung/llama2_7b_openorca_35k", device_map="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use georgesung/llama2_7b_openorca_35k with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "georgesung/llama2_7b_openorca_35k"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "georgesung/llama2_7b_openorca_35k",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/georgesung/llama2_7b_openorca_35k

SGLang

How to use georgesung/llama2_7b_openorca_35k 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 "georgesung/llama2_7b_openorca_35k" \
    --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": "georgesung/llama2_7b_openorca_35k",
		"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 "georgesung/llama2_7b_openorca_35k" \
        --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": "georgesung/llama2_7b_openorca_35k",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use georgesung/llama2_7b_openorca_35k with Docker Model Runner:
```
docker model run hf.co/georgesung/llama2_7b_openorca_35k
```

llama2_7b_openorca_35k

Commit History

Update URL for fine-tuning guide

b3a16b5
verified

georgesung commited on 28 days ago

Adding `safetensors` variant of this model (#1)

0fdbcce
verified

georgesung

SFconvertbot commited on Apr 14, 2025

Create README.md

dd775f6

georgesung commited on Aug 20, 2023

Add model

f7bf90b

georgesung commited on Aug 10, 2023

initial commit

3ac8c9a

georgesung commited on Aug 9, 2023

Commit History

Update URL for fine-tuning guide b3a16b5 verified

Adding `safetensors` variant of this model (#1) 0fdbcce verified

Create README.md dd775f6

Add model f7bf90b

initial commit 3ac8c9a

Update URL for fine-tuning guide

b3a16b5
verified

Adding `safetensors` variant of this model (#1)

0fdbcce
verified

Create README.md

dd775f6

Add model

f7bf90b

initial commit

3ac8c9a