Text Generation
Transformers
PyTorch
English
t5
text2text-generation
Generated from Trainer
instruction fine-tuning
text-generation-inference
Instructions to use MBZUAI/LaMini-T5-61M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MBZUAI/LaMini-T5-61M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MBZUAI/LaMini-T5-61M")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MBZUAI/LaMini-T5-61M") model = AutoModelForSeq2SeqLM.from_pretrained("MBZUAI/LaMini-T5-61M") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use MBZUAI/LaMini-T5-61M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MBZUAI/LaMini-T5-61M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MBZUAI/LaMini-T5-61M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MBZUAI/LaMini-T5-61M
- SGLang
How to use MBZUAI/LaMini-T5-61M 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 "MBZUAI/LaMini-T5-61M" \ --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": "MBZUAI/LaMini-T5-61M", "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 "MBZUAI/LaMini-T5-61M" \ --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": "MBZUAI/LaMini-T5-61M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MBZUAI/LaMini-T5-61M with Docker Model Runner:
docker model run hf.co/MBZUAI/LaMini-T5-61M
Librarian Bot: Add base_model information to model
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by librarian-bot - opened
README.md
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license: cc-by-nc-4.0
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tags:
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- instruction fine-tuning
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results: []
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language:
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pipeline_tag: text2text-generation
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how can I become more healthy?
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example_title: example
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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license: cc-by-nc-4.0
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tags:
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- instruction fine-tuning
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pipeline_tag: text2text-generation
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widget:
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example_title: example
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base_model: t5-small
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model-index:
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- name: flan-t5-small-distil-v2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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