Text Generation
Transformers
Safetensors
English
t5
text2text-generation
fineweb
text-generation-inference
Instructions to use pszemraj/tFINE-base-300m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pszemraj/tFINE-base-300m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="pszemraj/tFINE-base-300m")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("pszemraj/tFINE-base-300m") model = AutoModelForSeq2SeqLM.from_pretrained("pszemraj/tFINE-base-300m") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use pszemraj/tFINE-base-300m with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pszemraj/tFINE-base-300m" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pszemraj/tFINE-base-300m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/pszemraj/tFINE-base-300m
- SGLang
How to use pszemraj/tFINE-base-300m 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 "pszemraj/tFINE-base-300m" \ --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": "pszemraj/tFINE-base-300m", "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 "pszemraj/tFINE-base-300m" \ --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": "pszemraj/tFINE-base-300m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use pszemraj/tFINE-base-300m with Docker Model Runner:
docker model run hf.co/pszemraj/tFINE-base-300m
Ctrl+K
- .hydra
- checkpoint-pt-10000
- checkpoint-pt-15000
- checkpoint-pt-20000
- checkpoint-pt-25000
- checkpoint-pt-30000
- checkpoint-pt-35000
- checkpoint-pt-40000
- checkpoint-pt-45000
- checkpoint-pt-5000
- checkpoint-pt-50000
- checkpoint-pt-55000
- checkpoint-pt-60000
- checkpoint-pt-65000
- checkpoint-pt-70000
- checkpoint-pt-75000
- checkpoint-pt-80000
- checkpoint-pt-80001
- tokenizer
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