Instructions to use Open-Orca/OpenOrcaxOpenChat-Preview2-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Open-Orca/OpenOrcaxOpenChat-Preview2-13B with Transformers:

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

pipe = pipeline("text-generation", model="Open-Orca/OpenOrcaxOpenChat-Preview2-13B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Open-Orca/OpenOrcaxOpenChat-Preview2-13B")
model = AutoModelForCausalLM.from_pretrained("Open-Orca/OpenOrcaxOpenChat-Preview2-13B")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Open-Orca/OpenOrcaxOpenChat-Preview2-13B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Open-Orca/OpenOrcaxOpenChat-Preview2-13B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Open-Orca/OpenOrcaxOpenChat-Preview2-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Open-Orca/OpenOrcaxOpenChat-Preview2-13B

SGLang

How to use Open-Orca/OpenOrcaxOpenChat-Preview2-13B 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 "Open-Orca/OpenOrcaxOpenChat-Preview2-13B" \
    --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": "Open-Orca/OpenOrcaxOpenChat-Preview2-13B",
		"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 "Open-Orca/OpenOrcaxOpenChat-Preview2-13B" \
        --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": "Open-Orca/OpenOrcaxOpenChat-Preview2-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Open-Orca/OpenOrcaxOpenChat-Preview2-13B with Docker Model Runner:
```
docker model run hf.co/Open-Orca/OpenOrcaxOpenChat-Preview2-13B
```

bleysg commited on Aug 4, 2023

Commit

ed00e88

1 Parent(s): 7f556f7

Update README.md

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@@ -74,7 +74,8 @@ Suffix (space after colon):
 ```
 <|end_of_turn|>\nAssistant:
 ```
-### Oobabooga's webui instructions can be found further down the page
 # Evaluation
@@ -154,6 +155,8 @@ Pre-quantized models are now available courtesy of our friend TheBloke:
 * **GGML**: https://huggingface.co/TheBloke/OpenOrcaxOpenChat-Preview2-13B-GGML
 * **GPTQ**: https://huggingface.co/TheBloke/OpenOrcaxOpenChat-Preview2-13B-GPTQ
 ## Serving with OpenChat
@@ -200,7 +203,9 @@ For "`Bot string`" ...
 ```
 Assistant:
 ```
-For "`Context`", it is not necessary but we have found good results with ...
 ```
 You are a helpful assistant. Please answer truthfully and write out your thinking step by step to be sure you get the right answer. If you make a mistake or encounter an error in your thinking, say so out loud and attempt to correct it. If you don't know or aren't sure about something, say so clearly. You will act as a professional logician, mathematician, and physicist. You will also act as the most appropriate type of expert to answer any particular question or solve the relevant problem; state which expert type your are, if so. Also think of any particular named expert that would be ideal to answer the relevant question or solve the relevant problem; name and act as them, if appropriate.
 ```

 ```
 <|end_of_turn|>\nAssistant:
 ```
+**Oobabooga's text-generation-webui instructions can be found [further down the page](https://huggingface.co/Open-Orca/OpenOrcaxOpenChat-Preview2-13B#serving-with-oobabooga--text-generation-webui).**
 # Evaluation
 * **GGML**: https://huggingface.co/TheBloke/OpenOrcaxOpenChat-Preview2-13B-GGML
 * **GPTQ**: https://huggingface.co/TheBloke/OpenOrcaxOpenChat-Preview2-13B-GPTQ
+The serving instructions below only apply to the unquantized model being presented in the repository you are viewing here.
+There are some notes, such as on use of the prompt format, that will still apply to the quantized models though.
 ## Serving with OpenChat
 ```
 Assistant:
 ```
+For "`Context`", this is analogous to system prompt.
+It is not necessary, but we have found good results with the below example.
+System prompts used in the Orca training also work well. ...
 ```
 You are a helpful assistant. Please answer truthfully and write out your thinking step by step to be sure you get the right answer. If you make a mistake or encounter an error in your thinking, say so out loud and attempt to correct it. If you don't know or aren't sure about something, say so clearly. You will act as a professional logician, mathematician, and physicist. You will also act as the most appropriate type of expert to answer any particular question or solve the relevant problem; state which expert type your are, if so. Also think of any particular named expert that would be ideal to answer the relevant question or solve the relevant problem; name and act as them, if appropriate.
 ```