Text Generation
Transformers
Safetensors
phi3
torchwright
compiled-transformer
calculator_scratchpad
text-generation-inference
Instructions to use physicsrob/torchwright-calculator-scratchpad-max-digits-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use physicsrob/torchwright-calculator-scratchpad-max-digits-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="physicsrob/torchwright-calculator-scratchpad-max-digits-3")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("physicsrob/torchwright-calculator-scratchpad-max-digits-3") model = AutoModelForCausalLM.from_pretrained("physicsrob/torchwright-calculator-scratchpad-max-digits-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use physicsrob/torchwright-calculator-scratchpad-max-digits-3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "physicsrob/torchwright-calculator-scratchpad-max-digits-3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "physicsrob/torchwright-calculator-scratchpad-max-digits-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/physicsrob/torchwright-calculator-scratchpad-max-digits-3
- SGLang
How to use physicsrob/torchwright-calculator-scratchpad-max-digits-3 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "physicsrob/torchwright-calculator-scratchpad-max-digits-3" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "physicsrob/torchwright-calculator-scratchpad-max-digits-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "physicsrob/torchwright-calculator-scratchpad-max-digits-3" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "physicsrob/torchwright-calculator-scratchpad-max-digits-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use physicsrob/torchwright-calculator-scratchpad-max-digits-3 with Docker Model Runner:
docker model run hf.co/physicsrob/torchwright-calculator-scratchpad-max-digits-3
Upload folder using huggingface_hub
Browse files- README.md +96 -0
- config.json +33 -0
- generation_config.json +6 -0
- model-00001-of-00019.safetensors +3 -0
- model-00002-of-00019.safetensors +3 -0
- model-00003-of-00019.safetensors +3 -0
- model-00004-of-00019.safetensors +3 -0
- model-00005-of-00019.safetensors +3 -0
- model-00006-of-00019.safetensors +3 -0
- model-00007-of-00019.safetensors +3 -0
- model-00008-of-00019.safetensors +3 -0
- model-00009-of-00019.safetensors +3 -0
- model-00010-of-00019.safetensors +3 -0
- model-00011-of-00019.safetensors +3 -0
- model-00012-of-00019.safetensors +3 -0
- model-00013-of-00019.safetensors +3 -0
- model-00014-of-00019.safetensors +3 -0
- model-00015-of-00019.safetensors +3 -0
- model-00016-of-00019.safetensors +3 -0
- model-00017-of-00019.safetensors +3 -0
- model-00018-of-00019.safetensors +3 -0
- model-00019-of-00019.safetensors +3 -0
- model.safetensors.index.json +1 -0
- tokenizer.json +130 -0
- tokenizer_config.json +8 -0
README.md
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| 1 |
+
---
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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_scratchpad
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+
pipeline_tag: text-generation
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+
---
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+
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# `calculator_scratchpad`, max_digits=3 (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_scratchpad` example built with `max_digits=3`: a computation graph for integer arithmetic (`A op B` with `op` in `+ - *`) that streams its serial carry/borrow work as visible thinking tokens before emitting the answer.
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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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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+
repo_id = 'physicsrob/torchwright-calculator-scratchpad-max-digits-3'
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| 30 |
+
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=96, 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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| 40 |
+
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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 3 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` | `<THINKING>…</THINKING>408` |
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+
| `7+8` | `<THINKING>…</THINKING>15` |
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+
| `999*999` | `<THINKING>…</THINKING>998001` |
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| `999+1` | `<THINKING>…</THINKING>1000` |
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+
| `999-123` | `<THINKING>…</THINKING>876` |
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+
| `123-999` | `<THINKING>…</THINKING>-876` |
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+
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+
The answer is preceded by a visible scratchpad between `<THINKING>` and
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+
`</THINKING>`: superscript glyphs (`⁰¹²`) stream the per-column carry /
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| 58 |
+
borrow / comparison state, plain digits are the unnormalized scratch answer,
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| 59 |
+
and subscript glyphs (`₀₁₂`) stream the leading-zero cleanup count. The
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final answer follows the closing tag — e.g. `999+1` ends
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`…</THINKING>1000`.
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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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| 69 |
+
## Verification
|
| 70 |
+
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| 71 |
+
The examples above are exact reference outputs. The Modal publishing path
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| 72 |
+
reloads the emitted checkpoint through stock `transformers`, checks those
|
| 73 |
+
examples plus additional width-limit cases against Python integer arithmetic,
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| 74 |
+
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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| 78 |
+
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The checkpoint stores 11.61 GB of dense fp32 weights (2,901,770,240 entries) at
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the example family's shared compile width. 99.99% 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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## Family
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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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| 94 |
+
thinking tokens) — are published at several digit widths. Browse the
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| 95 |
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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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config.json
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{
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"architectures": [
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"Phi3ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 15,
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"embd_pdrop": 0.0,
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"eos_token_id": 16,
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 8192,
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"initializer_range": 0.02,
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"intermediate_size": 2121,
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"max_position_embeddings": 512,
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"model_type": "phi3",
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"num_attention_heads": 52,
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"num_hidden_layers": 18,
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"num_key_value_heads": 52,
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"original_max_position_embeddings": 4096,
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"pad_token_id": null,
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"resid_pdrop": 0.0,
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"rms_norm_eps": 1e-05,
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"rope_parameters": {
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"partial_rotary_factor": 1.0,
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"rope_theta": 500000.0,
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"rope_type": "default"
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},
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"sliding_window": null,
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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": 33
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}
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generation_config.json
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{
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"bos_token_id": 15,
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"eos_token_id": 16,
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"pad_token_id": 16,
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"transformers_version": "5.12.1"
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}
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| 123 |
+
"₄ ": 29,
|
| 124 |
+
"₅ ": 30,
|
| 125 |
+
"₆ ": 31,
|
| 126 |
+
"</THINKING>": 32
|
| 127 |
+
},
|
| 128 |
+
"unk_token": "<unk>"
|
| 129 |
+
}
|
| 130 |
+
}
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"backend": "tokenizers",
|
| 3 |
+
"bos_token": "<bos>",
|
| 4 |
+
"eos_token": "<eos>",
|
| 5 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 6 |
+
"tokenizer_class": "TokenizersBackend",
|
| 7 |
+
"unk_token": null
|
| 8 |
+
}
|