Download KenLM at server startup, not Docker build

Enable KenLM domain-LM shallow fusion at decode time (#1)

Run model fp32 on GPU (fp16 produced degenerate logits)

Upcast fp16 logits to fp32 before pyctcdecode (fixes empty-beam error)

Use GPU when available (fp16 + autocast for T4)

Tune for speed: beam_width 8->4, hotword_weight 10->5

Fix IndentationError: collapse duplicated regex lines

Debug log + handle SentencePiece-prefixed brace tokens

Convert MedASR </s> sentence-boundary token to period

Mark pad token as CTC blank for pyctcdecode (fix off-by-one)

Fix decoder vocab-size mismatch (use model.config.vocab_size)

Beam search + radiology hotwords + /transcribe-pcm endpoint

Upload server.py with huggingface_hub

Upload server.py with huggingface_hub

Upload server.py with huggingface_hub

Upload folder using huggingface_hub