Instructions to use Isotonic/gpt-human-assistant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Isotonic/gpt-human-assistant with Transformers:

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

pipe = pipeline("text-generation", model="Isotonic/gpt-human-assistant")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Isotonic/gpt-human-assistant")
model = AutoModelForCausalLM.from_pretrained("Isotonic/gpt-human-assistant")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Isotonic/gpt-human-assistant with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Isotonic/gpt-human-assistant

SGLang

How to use Isotonic/gpt-human-assistant 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 "Isotonic/gpt-human-assistant" \
    --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": "Isotonic/gpt-human-assistant",
		"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 "Isotonic/gpt-human-assistant" \
        --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": "Isotonic/gpt-human-assistant",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Isotonic/gpt-human-assistant with Docker Model Runner:
```
docker model run hf.co/Isotonic/gpt-human-assistant
```

librarian-bot commited on Mar 16, 2023

Commit

d314b2d

1 Parent(s): e169233

Librarian Bot: Update dataset YAML metadata for model

Browse files

This is a pull request to add a dataset, [`Isotonic/human_assistant_conversation`](https://huggingface.co/datasets/Isotonic/human_assistant_conversation), to the metadata for your model (defined in the `YAML` block of your model's `README.md`).
The pull request was made by [librarian-bot](https://huggingface.co/librarian-bot) and used a combination of rules and/or machine learning to suggest this additional metadata.
If this suggestion is incorrect, feel free to close this pull request.

Librarian Bot was made by [@davanstrien](https://huggingface.co/davanstrien); feel free to get in touch with feedback.

Files changed (1) hide show

README.md +1 -0

README.md CHANGED Viewed

@@ -2,6 +2,7 @@
 license: mit
 tags:
 - generated_from_trainer
 metrics:
 - accuracy
 model-index:

 license: mit
 tags:
 - generated_from_trainer
+datasets: Isotonic/human_assistant_conversation
 metrics:
 - accuracy
 model-index: