Text Generation
Transformers
TensorBoard
Safetensors
t5la
Generated from Trainer
Eval Results (legacy)
Instructions to use hrezaei/T5La-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hrezaei/T5La-Large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hrezaei/T5La-Large")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("hrezaei/T5La-Large", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use hrezaei/T5La-Large with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hrezaei/T5La-Large" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hrezaei/T5La-Large", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/hrezaei/T5La-Large
- SGLang
How to use hrezaei/T5La-Large 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 "hrezaei/T5La-Large" \ --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": "hrezaei/T5La-Large", "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 "hrezaei/T5La-Large" \ --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": "hrezaei/T5La-Large", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use hrezaei/T5La-Large with Docker Model Runner:
docker model run hf.co/hrezaei/T5La-Large
| timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue | |
| 2025-09-11T02:40:34,codecarbon,b04c1563-5d62-42a8-8bc6-93477c9000b6,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,154498.23274948914,0.8864457043666151,5.737578278995209e-06,189.27498938396408,288.2014966944229,38.0,8.205427766058628,11.91442283986396,1.662818133888643,21.782668739811157,Sweden,SWE,dalarna county,,,Linux-4.18.0-553.56.1.el8_10.x86_64-x86_64-with-glibc2.28,3.10.18,3.0.4,16,AMD EPYC 7413 24-Core Processor,1,1 x NVIDIA H100 PCIe,15.6326,60.6043,85.84,machine,N,1.0 | |