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  1. README.md +89 -0
  2. config.json +33 -0
  3. generation_config.json +6 -0
  4. model-00001-of-00034.safetensors +3 -0
  5. model-00002-of-00034.safetensors +3 -0
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  38. model.safetensors.index.json +1 -0
  39. tokenizer.json +114 -0
  40. tokenizer_config.json +8 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ library_name: transformers
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+ tags:
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+ - torchwright
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+ - compiled-transformer
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+ - calculator_simple
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # `calculator_simple`, max_digits=6 (torchwright)
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+
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+ A **compiled** transformer: the
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+ [torchwright](https://github.com/physicsrob/torchwright) compiler emitted
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+ these weights directly from a computation graph — nothing was trained. This
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+ bundle is the `calculator_simple` example built with `max_digits=6`: a computation graph for integer arithmetic (`A op B` with `op` in `+ - *`).
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+
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+ The bundle uses the stock Phi-3 architecture and loads through `transformers`
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+ without custom model code or `trust_remote_code`.
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+
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+ Run it in **fp32** with **greedy decoding** (`do_sample=False`). Other
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+ precisions and decoding modes are outside the supported contract.
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+
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+ ## Usage
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ repo_id = 'physicsrob/torchwright-calculator-simple-max-digits-6'
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+ model = AutoModelForCausalLM.from_pretrained(repo_id).eval()
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+ tok = AutoTokenizer.from_pretrained(repo_id)
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+
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+ enc = tok('12*34\n', return_tensors="pt")
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+ out = model.generate(enc["input_ids"], max_new_tokens=32, do_sample=False,
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+ eos_token_id=tok.eos_token_id, pad_token_id=tok.eos_token_id)
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+ print(tok.decode(out[0, enc["input_ids"].shape[1]:], skip_special_tokens=True))
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+ ```
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+
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+ ## Input and output
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+
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+ Prompts are `A op B` terminated by a newline: two non-negative decimal
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+ operands of up to 6 digits, with `op` one of `+`, `-`, `*`.
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+ Subtraction may produce a negative result. Wider operands, or any character
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+ outside the model's small vocabulary, are outside the contract — the output
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+ is undefined.
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+
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+ | prompt | output |
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+ |---|---|
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+ | `12*34` | `408` |
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+ | `7+8` | `15` |
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+ | `999999*999999` | `999998000001` |
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+ | `999999+1` | `1000000` |
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+ | `999999-123456` | `876543` |
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+ | `123456-999999` | `-876543` |
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+
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+ ## Intended use and limitations
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+
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+ This model is a demonstration of a computation graph compiled into transformer
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+ weights. It is not a general language model or a general-purpose calculator;
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+ only the input contract above is supported.
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+
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+ ## Verification
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+
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+ The examples above are exact reference outputs. The Modal publishing path
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+ reloads the emitted checkpoint through stock `transformers`, checks those
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+ examples plus additional width-limit cases against Python integer arithmetic,
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+ and refuses to upload on a mismatch. This is a functional smoke test, not
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+ exhaustive verification of every allowed expression.
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+
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+ ## Size
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+
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+ The checkpoint stores 61.67 GB of dense fp32 weights (15,416,598,528 entries) at
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+ the example family's shared compile width. 100.00% of those entries are
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+ exactly zero: the vast majority of the model is unused canvas, so size reflects
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+ the compile geometry rather than stored knowledge.
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+
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+ The zero entries are not compressed, and dense `transformers` execution still
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+ pays their memory and compute cost. CPU execution is supported; allow
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+ additional RAM beyond the checkpoint size.
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+
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+ ## Family
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+
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+ One example of many compiled with torchwright. Calculator siblings —
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+ `calculator-simple` (serial arithmetic, depth grows with the digit count),
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+ `calculator-advanced` (carry-lookahead, near-flat depth), and
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+ `calculator-scratchpad` (flat depth; the serial work streams out as visible
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+ thinking tokens) — are published at several digit widths. Browse the
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+ [torchwright calculator models](https://huggingface.co/models?search=physicsrob%2Ftorchwright-calculator)
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+ on Hugging Face.
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+ "tie_word_embeddings": true,
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+ "transformers_version": "5.12.1",
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+ "use_cache": true,
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+ "vocab_size": 17
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+ }
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