Instructions to use huggingtweets/holocenite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingtweets/holocenite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="huggingtweets/holocenite")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("huggingtweets/holocenite") model = AutoModelForCausalLM.from_pretrained("huggingtweets/holocenite", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use huggingtweets/holocenite with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "huggingtweets/holocenite" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "huggingtweets/holocenite", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/huggingtweets/holocenite
- SGLang
How to use huggingtweets/holocenite 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/holocenite" \ --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/holocenite", "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/holocenite" \ --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/holocenite", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use huggingtweets/holocenite with Docker Model Runner:
docker model run hf.co/huggingtweets/holocenite
Commit History
-
Update model preview
c9d4cc9 -
Update model preview
e625912 -
Update model preview
e0ef592 -
New model from https://wandb.ai/wandb/huggingtweets/runs/1zuygzmm
a595b99
-
upload flax model
254725e -
allow flax
8a2d483
-
Update model preview
b78a57e -
New model from https://wandb.ai/wandb/huggingtweets/runs/2be3kska
50ca760
-
Update README.md
4cd227c -
Update merges.txt
33fcf3e -
Update tokenizer_config.json
7ef386d -
Update config.json
fb819ed -
Update pytorch_model.bin
b9d40f7 -
Update special_tokens_map.json
1e9418d -
Update README.md
f65ce7c -
Update vocab.json
8094176 -
initial commit
ba80e1d