Instructions to use pankajmathur/orca_mini_v3_70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pankajmathur/orca_mini_v3_70b with Transformers:

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

pipe = pipeline("text-generation", model="pankajmathur/orca_mini_v3_70b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pankajmathur/orca_mini_v3_70b")
model = AutoModelForCausalLM.from_pretrained("pankajmathur/orca_mini_v3_70b")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use pankajmathur/orca_mini_v3_70b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pankajmathur/orca_mini_v3_70b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pankajmathur/orca_mini_v3_70b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/pankajmathur/orca_mini_v3_70b

SGLang

How to use pankajmathur/orca_mini_v3_70b 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 "pankajmathur/orca_mini_v3_70b" \
    --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": "pankajmathur/orca_mini_v3_70b",
		"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 "pankajmathur/orca_mini_v3_70b" \
        --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": "pankajmathur/orca_mini_v3_70b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use pankajmathur/orca_mini_v3_70b with Docker Model Runner:
```
docker model run hf.co/pankajmathur/orca_mini_v3_70b
```

orca_mini_v3_70b

Commit History

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pankajmathur commited on Aug 10, 2023

Commit History

Adding `safetensors` variant of this model (#9) 1cf8a82 verified

Update README.md 84cd92e verified

Adding Evaluation Results (#8) cd2a32b verified

Update README.md ca1181a verified

Adding Evaluation Results (#7) e8e856d verified

Adding Evaluation Results (#6) 01e7875

Update README.md 5f990de

Update README.md 5f3d251

Update README.md 5267da9

Upload orca_minis_small.jpeg 5a5e842

Update README.md f1458f9

Update README.md c1d4f99

Update README.md 15d6291

Create README.md d0afcea

Initial Commit f2eda76

initial commit 7090d55

Adding `safetensors` variant of this model (#9)

1cf8a82
verified

Update README.md

84cd92e
verified

Adding Evaluation Results (#8)

cd2a32b
verified

Update README.md

ca1181a
verified

Adding Evaluation Results (#7)

e8e856d
verified

Adding Evaluation Results (#6)

01e7875

Update README.md

5f990de

Update README.md

5f3d251

Update README.md

5267da9

Upload orca_minis_small.jpeg

5a5e842

Update README.md

f1458f9

Update README.md

c1d4f99

Update README.md

15d6291

Create README.md

d0afcea

Initial Commit

f2eda76

initial commit

7090d55