Fix pipeline_tag; add accuracy chart, GitHub link, PDF report
Browse files- .gitattributes +2 -0
- README.md +6 -1
- accuracy_by_category.png +3 -0
- nano-dates-report.pdf +3 -0
.gitattributes
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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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accuracy_by_category.png filter=lfs diff=lfs merge=lfs -text
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nano-dates-report.pdf filter=lfs diff=lfs merge=lfs -text
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README.md
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@@ -9,7 +9,7 @@ tags:
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- structured-output
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- byte-level
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- from-scratch
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pipeline_tag:
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library_name: safetensors
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---
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@@ -31,6 +31,11 @@ The model is given a **reference date** (`today`) at the start of the prompt, so
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relative phrases ("tomorrow", "in 3 weeks") are computable from the input alone —
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it never needs a wall clock.
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## Why this exists
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A 1M-parameter model can't be a general assistant, but it *can* completely nail a
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- structured-output
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- byte-level
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- from-scratch
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pipeline_tag: text-generation
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library_name: safetensors
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---
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relative phrases ("tomorrow", "in 3 weeks") are computable from the input alone —
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it never needs a wall clock.
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**Code, training, and reproduction:** https://github.com/vukrosic/nano-dates
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(self-contained `train.py` / `eval.py` / data generator / tests + a PDF report).
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## Why this exists
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A 1M-parameter model can't be a general assistant, but it *can* completely nail a
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accuracy_by_category.png
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Git LFS Details
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nano-dates-report.pdf
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:68cee35c5950926f249cdb4728ca4c7a3a85d212be275d54d3e93c666ff71c58
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size 162814
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