Text Generation
Transformers
Safetensors
English
t5
text2text-generation
sentiment-analysis
target-sentiment-analysis
reasoning
text-generation-inference
Instructions to use nicolay-r/flan-t5-tsa-thor-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nicolay-r/flan-t5-tsa-thor-xl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nicolay-r/flan-t5-tsa-thor-xl")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nicolay-r/flan-t5-tsa-thor-xl") model = AutoModelForSeq2SeqLM.from_pretrained("nicolay-r/flan-t5-tsa-thor-xl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use nicolay-r/flan-t5-tsa-thor-xl with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nicolay-r/flan-t5-tsa-thor-xl" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nicolay-r/flan-t5-tsa-thor-xl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/nicolay-r/flan-t5-tsa-thor-xl
- SGLang
How to use nicolay-r/flan-t5-tsa-thor-xl 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 "nicolay-r/flan-t5-tsa-thor-xl" \ --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": "nicolay-r/flan-t5-tsa-thor-xl", "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 "nicolay-r/flan-t5-tsa-thor-xl" \ --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": "nicolay-r/flan-t5-tsa-thor-xl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use nicolay-r/flan-t5-tsa-thor-xl with Docker Model Runner:
docker model run hf.co/nicolay-r/flan-t5-tsa-thor-xl
- Xet hash:
- 55fa5df3d3d5815368a3a95b39fb8867f390360b3fbced3806f9d58e2cc96ad1
- Size of remote file:
- 715 MB
- SHA256:
- 0f74f6415749d463dbaf08d13435ffbb1f41ef817c9b07d4f7e6c1008410cf47
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