YAML Metadata Warning:The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

tinycode-narrator

Accepted TinyCode model, based on Tern 124M. Python code -> steps -> summary. The ONNX graph includes the snippet LoRA adapter; native inference needs both checkpoint.pt and snippet_adapter.pt. Functions use the unchanged function checkpoint.

Files

model.onnx: complete FP32 browser inference graph, no external tensor files.
manifest.json: SHA-256, graph dimensions and inference settings.
checkpoint.pt: native PyTorch model (custom Tern architecture, not Transformers AutoModel).
runtime/codenarrator/: Python architecture, tokenizer, preprocessing and decoding implementation.
gpt2.tiktoken: complete GPT-2 mergeable token ranks (base64 token + rank).
tinycode_config.json: architecture and task settings.

Upload ALL contents of this folder to the ROOT of a public Hugging Face model repository. Keep filenames unchanged. The website downloads model.onnx using https://huggingface.co/USERNAME/REPO/resolve/main/model.onnx. The native checkpoints are provided for reproducibility; they are not downloaded by the website. No hosted inference server is needed. Weights execute on the visitor's CPU via ONNX Runtime Web.

Original pretraining model: https://huggingface.co/mikahniehaus/Tern .

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