| """Package the trained webLTM weights for a Hugging Face model repo: |
| config.json + model.safetensors (no pickle), ready for |
| `huggingface-cli upload`.""" |
| import json |
| import numpy as np |
| from safetensors.numpy import save_file |
|
|
| with open("/home/claude/webLTM/eval/weights.json") as f: |
| data = json.load(f) |
|
|
| tensors = {k: np.array(v, dtype=np.float32) for k, v in data["weights"].items()} |
| save_file(tensors, "/home/claude/webLTM/hf/model.safetensors") |
|
|
| config = { |
| "architecture": "webLTM-recurrent-depth", |
| "vocab": data["vocab"], |
| "seq_len": data["seq_len"], |
| "ans_start": data["ans_start"], |
| "digits_per_operand": data["d"], |
| "d_model": data["d_model"], |
| "n_heads": data["n_heads"], |
| "n_blocks": 3, |
| "block_order": ["prelude", "core", "coda"], |
| "recurrent_block": "core", |
| "trained_recurrence_range": [1, 8], |
| "task": "non-autoregressive multi-digit addition", |
| "params": sum(t.size for t in tensors.values()), |
| } |
| with open("/home/claude/webLTM/hf/config.json", "w") as f: |
| json.dump(config, f, indent=2) |
|
|
| print("params:", config["params"]) |
| print("tensors:", len(tensors)) |
|
|
