Instructions to use huggingtweets/plesmasquerade with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingtweets/plesmasquerade with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="huggingtweets/plesmasquerade")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("huggingtweets/plesmasquerade") model = AutoModelForCausalLM.from_pretrained("huggingtweets/plesmasquerade", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use huggingtweets/plesmasquerade with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "huggingtweets/plesmasquerade" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "huggingtweets/plesmasquerade", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/huggingtweets/plesmasquerade
- SGLang
How to use huggingtweets/plesmasquerade 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/plesmasquerade" \ --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/plesmasquerade", "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/plesmasquerade" \ --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/plesmasquerade", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use huggingtweets/plesmasquerade with Docker Model Runner:
docker model run hf.co/huggingtweets/plesmasquerade
Commit History
-
Update model preview
de995e6 -
Update model preview
e615c02 -
Update model preview
fc8f13d -
Update model preview
f38c32e -
Update model preview
4d78fcb -
Update model preview
ecb33f2 -
Update model preview
bb156ca -
Update model preview
b22f6d5 -
Update model preview
9452524 -
New model from https://wandb.ai/wandb/huggingtweets/runs/6jt0gb2r
52afe81
-
upload flax model
00560e3 -
allow flax
34808f0
-
Update model preview
e98fab1 -
Update model preview
762a920 -
New model from https://wandb.ai/wandb/huggingtweets/runs/2kpl5ujc
860ea6a
-
New model from https://wandb.ai/wandb/huggingtweets/runs/mgfzci45
75da966
-
Update model preview
29508d8 -
New model from https://wandb.ai/wandb/huggingtweets/runs/1lxt2vhw
cf7e88c -
Update model preview
a1cf630 -
Update model preview
fb7b80a -
Update model preview
07918bb -
Update model preview
3ba8004 -
Update model preview
e9d963d -
Update model preview
e897317 -
Update model preview
8bd54f6 -
Update model preview
808e8c4 -
Update model preview
a85ecaf -
Update model preview
87a898a -
Update model preview
437a7ba -
Update model preview
26328c4 -
New model from https://wandb.ai/wandb/huggingtweets/runs/smhs5w04
ce223f4
-
Update model preview
efc508b -
Update model preview
cfe5fc0 -
Update model preview
10e5394 -
Update model preview
b605eb6 -
New model from https://wandb.ai/wandb/huggingtweets/runs/1u49vusi
167cc15 -
Update model preview
6b9e65f -
Update model preview
2da5267 -
New model from https://wandb.ai/wandb/huggingtweets/runs/4sdtkl5t
43169e0 -
initial commit
943b98e