Instructions to use AlanRobotics/ruT5_q_a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlanRobotics/ruT5_q_a with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AlanRobotics/ruT5_q_a")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AlanRobotics/ruT5_q_a") model = AutoModelForSeq2SeqLM.from_pretrained("AlanRobotics/ruT5_q_a") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use AlanRobotics/ruT5_q_a with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AlanRobotics/ruT5_q_a" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AlanRobotics/ruT5_q_a", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AlanRobotics/ruT5_q_a
- SGLang
How to use AlanRobotics/ruT5_q_a 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 "AlanRobotics/ruT5_q_a" \ --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": "AlanRobotics/ruT5_q_a", "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 "AlanRobotics/ruT5_q_a" \ --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": "AlanRobotics/ruT5_q_a", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AlanRobotics/ruT5_q_a with Docker Model Runner:
docker model run hf.co/AlanRobotics/ruT5_q_a
Commit ·
144eeb1
1
Parent(s): 7b7af6b
Upload tokenizer
Browse files- special_tokens_map.json +3 -5
- spiece.model +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +10 -13
special_tokens_map.json
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"unk_token": "[UNK]"
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"eos_token": "</s>",
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spiece.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:49e3442998423498b1c036276787f7d065fa673d76b9dafb83bd5fa19d17a6c5
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size 742072
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tokenizer.json
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tokenizer_config.json
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"name_or_path": "AlanRobotics/
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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"additional_special_tokens": null,
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"eos_token": "</s>",
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"extra_ids": 0,
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"model_max_length": 1000000000000000019884624838656,
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"name_or_path": "AlanRobotics/ruT5-base",
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"pad_token": "<pad>",
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"sp_model_kwargs": {},
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"special_tokens_map_file": "/Users/alanbarsag/.cache/huggingface/hub/models--AlanRobotics--ruT5-base/snapshots/06d1ee6609acbe036c7699aa744d6aca561e7a85/special_tokens_map.json",
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"tokenizer_class": "T5Tokenizer",
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"unk_token": "<unk>"
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