README.md

metadata

title: TR-Hash Tiny
emoji: 🧭
colorFrom: purple
colorTo: green
sdk: docker
app_port: 7860
pinned: false
license: apache-2.0
models:
  - AETHORIA-AI/TR-HASH-MoE-200M-160B-SFT

TR-Hash Tiny · TR-HASH MoE 200M Full SFT

OpenAI-compatible chat API serving the PIQA-selected epoch-3 root weights from AETHORIA-AI/TR-HASH-MoE-200M-160B-SFT with Complexity-ML/TR-Hash-i64.

This is a full-parameter SFT, not a LoRA adapter. All 201.2M parameters were trained for three epochs on the audited 300K SFT v2 mixture. Epoch 3 scores 68.01% PIQA accuracy and 69.21% length-normalized accuracy on the full 1,838-example validation set in the MLX FP16 cross-check.

The launcher intentionally downloads only the release files at the model-repo root. The three large resumable step_* training folders are excluded. The bundled chat_template.jinja and tokenizer are loaded beside the single root model.safetensors.

curl https://pacific-i64-tr-hash-tiny.hf.space/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tr-hash-moe-200m",
    "messages": [{"role": "user", "content": "Explain why 17 × 23 − 14 equals 377."}],
    "max_tokens": 1024,
    "temperature": 0.15,
    "top_k": 10,
    "top_p": 0.85,
    "repetition_penalty": 1.02,
    "frequency_penalty": 0.0,
    "stream": false
  }'

The CPU deployment uses continuous batching, paged KV caching, prefix caching, streaming and rolling context compaction at 1,024 prompt tokens. It also supports optional dynamic INT8 packing of linear layers. Set the Space variable CPU_INT8=false to serve floating-point weights.

Endpoints: /health, /v1/models, /v1/completions, /v1/chat/completions, /v1/metrics, /v1/monitor, /v1/experts.