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humarin-paraphraser-handler
Custom HF Inference Endpoint handler that wraps
humarin/chatgpt_paraphraser_on_T5_base
with explicit T5ForConditionalGeneration + diverse beam search,
so HF auto-routing cannot mis-load it as a causal LM.
Why this exists
When deployed directly, HF Inference Endpoints routed the base model to vLLM / TGI, which treats T5 as causal generation and produces broken output (echoes the input prompt instead of returning a paraphrase).
This repo only ships handler.py + requirements.txt; the model weights
are loaded at runtime from the base repo.
API
POST with JSON body:
{
"inputs": "The product is excellent and works well.",
"parameters": {
"num_beams": 5,
"num_beam_groups": 5,
"num_return_sequences": 5,
"diversity_penalty": 3.0,
"repetition_penalty": 10.0,
"no_repeat_ngram_size": 2,
"max_length": 128
}
}
Returns 5 paraphrase candidates as [{"generated_text": ...}, ...].
Model tree for singoojiang/humarin-paraphraser-handler
Base model
google-t5/t5-base