Instructions to use crumb/gpt-j-6b-finetune-super-glue with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use crumb/gpt-j-6b-finetune-super-glue with Transformers:

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

pipe = pipeline("text-generation", model="crumb/gpt-j-6b-finetune-super-glue")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("crumb/gpt-j-6b-finetune-super-glue")
model = AutoModelForMultimodalLM.from_pretrained("crumb/gpt-j-6b-finetune-super-glue")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use crumb/gpt-j-6b-finetune-super-glue with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "crumb/gpt-j-6b-finetune-super-glue"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "crumb/gpt-j-6b-finetune-super-glue",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/crumb/gpt-j-6b-finetune-super-glue

SGLang

How to use crumb/gpt-j-6b-finetune-super-glue 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 "crumb/gpt-j-6b-finetune-super-glue" \
    --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": "crumb/gpt-j-6b-finetune-super-glue",
		"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 "crumb/gpt-j-6b-finetune-super-glue" \
        --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": "crumb/gpt-j-6b-finetune-super-glue",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use crumb/gpt-j-6b-finetune-super-glue with Docker Model Runner:
```
docker model run hf.co/crumb/gpt-j-6b-finetune-super-glue
```

mia naomi commited on Jul 17, 2022

Commit

f44bace

1 Parent(s): 5cf66af

Update README.md

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@@ -11,6 +11,8 @@ tags:
 inference: false
 ---
 see [this repo](https://huggingface.co/crumb/gpt-j-6b-shakespeare) for more information, finetuned with [8-bit Adam](https://arxiv.org/abs/2110.02861) on custom transformed super glue tasks, transformed somewhat like the [T0 paper](https://arxiv.org/abs/2110.08207)
 ```python

 inference: false
 ---
+side project, not final working good product
 see [this repo](https://huggingface.co/crumb/gpt-j-6b-shakespeare) for more information, finetuned with [8-bit Adam](https://arxiv.org/abs/2110.02861) on custom transformed super glue tasks, transformed somewhat like the [T0 paper](https://arxiv.org/abs/2110.08207)
 ```python