Text Generation
Transformers
Safetensors
English
t5
text2text-generation
pinterest
keywords
personality
fine-tuned
lora
flan-t5
text-generation-inference
Instructions to use Amama02/pinterest-personality-keywords-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amama02/pinterest-personality-keywords-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Amama02/pinterest-personality-keywords-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Amama02/pinterest-personality-keywords-v3") model = AutoModelForSeq2SeqLM.from_pretrained("Amama02/pinterest-personality-keywords-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Amama02/pinterest-personality-keywords-v3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Amama02/pinterest-personality-keywords-v3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Amama02/pinterest-personality-keywords-v3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Amama02/pinterest-personality-keywords-v3
- SGLang
How to use Amama02/pinterest-personality-keywords-v3 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 "Amama02/pinterest-personality-keywords-v3" \ --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": "Amama02/pinterest-personality-keywords-v3", "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 "Amama02/pinterest-personality-keywords-v3" \ --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": "Amama02/pinterest-personality-keywords-v3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Amama02/pinterest-personality-keywords-v3 with Docker Model Runner:
docker model run hf.co/Amama02/pinterest-personality-keywords-v3
Upload model_metadata.json with huggingface_hub
Browse files- model_metadata.json +19 -0
model_metadata.json
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{
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"model_info": {
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"base_model": "google/flan-t5-base",
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"fine_tuning_method": "LoRA",
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"generation_parameters": {
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"max_length": 300,
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"num_beams": 8,
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"temperature": 0.9,
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"do_sample": true,
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"top_p": 0.95,
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"repetition_penalty": 2.0,
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"length_penalty": 1.2,
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"early_stopping": true,
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"no_repeat_ngram_size": 2
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},
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"deployment_date": "2025-08-07 22:49:21",
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"torch_dtype": "torch.float16"
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}
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}
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