Text Generation
Transformers
PyTorch
Safetensors
Russian
t5
text2text-generation
instruct
text-generation-inference
Instructions to use d0rj/FRED-T5-large-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use d0rj/FRED-T5-large-instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="d0rj/FRED-T5-large-instruct")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("d0rj/FRED-T5-large-instruct") model = AutoModelForSeq2SeqLM.from_pretrained("d0rj/FRED-T5-large-instruct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use d0rj/FRED-T5-large-instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "d0rj/FRED-T5-large-instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "d0rj/FRED-T5-large-instruct", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/d0rj/FRED-T5-large-instruct
- SGLang
How to use d0rj/FRED-T5-large-instruct 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 "d0rj/FRED-T5-large-instruct" \ --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": "d0rj/FRED-T5-large-instruct", "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 "d0rj/FRED-T5-large-instruct" \ --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": "d0rj/FRED-T5-large-instruct", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use d0rj/FRED-T5-large-instruct with Docker Model Runner:
docker model run hf.co/d0rj/FRED-T5-large-instruct
Commit History
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Добавил ссылку на оригинальную модель и указал количество токенов в обучающем сетеbfb1acf -
Merge branch 'main' of https://huggingface.co/d0rj/FRED-T5-large-instruct
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feat: add safetensors variant
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feat: delete old safetensors weights
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feat: update to step 1480
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (9a7c033a2b9e9cb712f274a34d9d12af595bde74) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>6ae0f58 -
docs: update README
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feat: add weights and states from 1120 step
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