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

Libraries

How to use YALCINKAYA/opsgenius_s with Transformers:

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

pipe = pipeline("text-generation", model="YALCINKAYA/opsgenius_s")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("YALCINKAYA/opsgenius_s")
model = AutoModelForCausalLM.from_pretrained("YALCINKAYA/opsgenius_s", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use YALCINKAYA/opsgenius_s with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/YALCINKAYA/opsgenius_s

SGLang

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

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

YALCINKAYA commited on Oct 14, 2024

Commit

31d95e5

verified ·

1 Parent(s): db85548

Training in progress, epoch 20

Browse files

Files changed (1) hide show

adapter_model.safetensors +1 -1

adapter_model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d0b4975d5c3d143f14113e4b802ec3d032cbf70e1b194de53069d8d0ba1d2d19
 size 10503408

 version https://git-lfs.github.com/spec/v1
+oid sha256:27227b0b53fbd6fed105b91e5be0658d339e9b44014d5dcb70125ba446293afe
 size 10503408