Instructions to use huggingtweets/iantdr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingtweets/iantdr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="huggingtweets/iantdr")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("huggingtweets/iantdr") model = AutoModelForCausalLM.from_pretrained("huggingtweets/iantdr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use huggingtweets/iantdr with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "huggingtweets/iantdr" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "huggingtweets/iantdr", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/huggingtweets/iantdr
- SGLang
How to use huggingtweets/iantdr 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/iantdr" \ --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/iantdr", "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/iantdr" \ --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/iantdr", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use huggingtweets/iantdr with Docker Model Runner:
docker model run hf.co/huggingtweets/iantdr
Download training_args.bin from huggingtweets/iantdr: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/huggingtweets/iantdr/resolve/main/training_args.bin
- Command line
-
hf download hf://huggingtweets/iantdr/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/huggingtweets/iantdr/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 4fc0ce46891eb21891fa8dbe0d566c5a7aa77af01f1f845699aa23b9547cd766
- Size of remote file:
- 3.31 kB
- SHA256:
- 9d87b0b555abc6e3529f5664c82f285606b0b5df583361aff26ef87d93de2ba8
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