Instructions to use huggingtweets/danielleboccell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingtweets/danielleboccell with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="huggingtweets/danielleboccell")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("huggingtweets/danielleboccell") model = AutoModelForCausalLM.from_pretrained("huggingtweets/danielleboccell", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use huggingtweets/danielleboccell with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "huggingtweets/danielleboccell" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "huggingtweets/danielleboccell", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/huggingtweets/danielleboccell
- SGLang
How to use huggingtweets/danielleboccell 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/danielleboccell" \ --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/danielleboccell", "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/danielleboccell" \ --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/danielleboccell", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use huggingtweets/danielleboccell with Docker Model Runner:
docker model run hf.co/huggingtweets/danielleboccell
Commit History
-
Update model preview
2d43bb5 -
New model from https://wandb.ai/wandb/huggingtweets/runs/3o514z49
0c6f770 -
Update model preview
206e9cc -
New model from https://wandb.ai/wandb/huggingtweets/runs/2p1rzfa3
7411da7
-
upload flax model
5874e72 -
allow flax
621bc89
-
Update model preview
2d6371d -
Update model preview
ee3980f -
Update model preview
c640fac -
Update model preview
5b0b80e -
New model from https://wandb.ai/wandb/huggingtweets/runs/2vhku1o1
22e8b10
-
Update model preview
2aa02fb -
Update model preview
6660c2a -
Update model preview
5dba713
-
Update model preview
3158d48 -
Update model preview
48b140c -
Update model preview
5d3b7ec -
Update model preview
68a11fb -
New model from https://wandb.ai/wandb/huggingtweets/runs/1eos8bct
aa82301 -
Update model preview
4d8959a -
New model from https://wandb.ai/wandb/huggingtweets/runs/1cmdsisc
aad0c73
-
Update model preview
dde4fc5 -
Update model preview
43d3ab8 -
New model from https://wandb.ai/wandb/huggingtweets/runs/2qt9cxfk
97ec52a -
New model from https://wandb.ai/wandb/huggingtweets/runs/1u9efgim
37126c5 -
Update model preview
3b03f00 -
Update model preview
9764633 -
New model from https://wandb.ai/wandb/huggingtweets/runs/2wj7scy2
e5e0f3c -
initial commit
a8c58ad