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

Libraries

How to use huggingtweets/pixiecatsupreme with Transformers:

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

pipe = pipeline("text-generation", model="huggingtweets/pixiecatsupreme")

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

tokenizer = AutoTokenizer.from_pretrained("huggingtweets/pixiecatsupreme")
model = AutoModelForCausalLM.from_pretrained("huggingtweets/pixiecatsupreme", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use huggingtweets/pixiecatsupreme with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/huggingtweets/pixiecatsupreme

SGLang

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

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

pixiecatsupreme

Commit History

Feb 22, 2025

23:45
Adding `safetensors` variant of this model⁠

SFconvertbot

Verified signature
560f3ff

May 22, 2021

18:50
upload flax model

patrickvonplaten

6ad4048
18:50
allow flax

patrickvonplaten

d736e87

Apr 7, 2021

10:18
Update model preview

boris

7d78b80
10:16
Update model preview

boris

442c317
10:13
Update model preview

boris

6c9b623
10:11
Update model preview

boris

a614e4c
10:09
Update model preview

boris

e457fd8
10:08
Update model preview

boris

6ce6e52
10:07
Update model preview

boris

d31f01d
10:06
Update model preview

boris

2bc5693
10:05
New model from https://wandb.ai/wandb/huggingtweets/runs/rbjnnywh

boris

a29fa88
10:05
initial commit

system HF Staff

66cdf09

Commit History

Feb 22, 2025

Adding `safetensors` variant of this model⁠

May 22, 2021

upload flax model

allow flax

Apr 7, 2021

Update model preview

Update model preview

Update model preview

Update model preview

Update model preview

Update model preview

Update model preview

Update model preview

New model from https://wandb.ai/wandb/huggingtweets/runs/rbjnnywh

initial commit