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211.
▲
Agentic Representation of Ecosystems
(github.com/offtrailstudio)
3 points
megabless123
3 months ago
1 comment
212.
▲
Show HN: Krnel-Graph, a Library for LLM representation engineering and control
(github.com/krnel-ai)
3 points
gcr
7 months ago
1 comment
213.
▲
Show HN: Create reproducible data analysis workflows with pytask
(github.com/pytask-dev)
3 points
robbitobbi
4 years ago
1 comment
214.
▲
Checkface: Represent hash as StyleGAN2 face, to make comparing hashes easy
(github.com/check-face)
3 points
melonmouse
5 years ago
1 comment
215.
▲
NetflixGraph: Compact in-memory representation of directed graph data
(netflix.github.com)
3 points
wallflower
13 years ago
discuss
216.
▲
Show HN: Reproducible experiments without committing every tweak
(github.com/DLR-Institute-of-Future-Fuels)
3 points
Saloc
2 days ago
discuss
217.
▲
A representation model as a workaround for catastrophic forgetting in LLMs
(gist.github.com)
3 points
dreamforever
a month ago
discuss
218.
▲
Show HN: oMLX – coding agents on local LLMs without the painful reprefill
(github.com/jundot)
3 points
jundot
3 months ago
discuss
219.
▲
Show HN: Do Models Represent Epistemic Stance?
(github.com/neelsomani)
3 points
nsomani
5 months ago
discuss
220.
▲
Reproducing GPT-2 (124M) in llm.c in 90 minutes for $20
(github.com/karpathy)
3 points
gmays
9 months ago
discuss
221.
▲
Show HN: LibPolyCall – Zero-Trust Polyglot FFI with Perfect State Reproduction
(github.com/obinexus)
3 points
obinexus
9 months ago
discuss
222.
▲
Show HN: Prompt-to-proof: reproducible LLM eval with hash-chained receipts
(github.com/kju4q)
3 points
Qendresahoti
9 months ago
discuss
223.
▲
Show HN: Bsdloader – Minimal (~123KB), reproducible x86_64 FreeBSD UEFI loader
(github.com/losfair)
3 points
losfair
9 months ago
discuss
224.
▲
Seed: CLI tool to quickly create directory structures from a tree representation
(github.com/jpwallace22)
3 points
thunderbong
a year ago
discuss
225.
▲
Reproducing GPT-2 (124M) in llm.c in 90 minutes for $20
(github.com/karpathy)
3 points
georgehill
2 years ago
discuss
226.
▲
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
(github.com/KimMeen)
3 points
teruakohatu
2 years ago
discuss
227.
▲
fst: Represent large sets and maps compactly with finite state transducers
(github.com/BurntSushi)
3 points
tosh
2 years ago
discuss
228.
▲
Rust lang adding privacy and reproducibility to compiler by default
(github.com/rust-lang)
3 points
transportheap
3 years ago
discuss
229.
▲
Pointer magic for efficient dynamic value representations
(nikic.github.com)
3 points
shakesbeard
14 years ago
discuss
230.
▲
Transform Python source code into it's most compact representation
(github.com/dflook)
3 points
rbanffy
4 years ago
discuss
231.
▲
Universal code for representing variable-length nonnegative integers in binary
(github.com/einar-saukas)
3 points
reidrac
5 years ago
discuss
232.
▲
Show HN: Urltron – represent JSON as clean url query parameters
(github.com/recurrency)
3 points
nojvek
5 years ago
discuss
233.
▲
Ask HN: How to make Rust release binaries reproducible/private?
3 points
_34vz
5 years ago
discuss
234.
▲
Show HN: Learning Node Representations That Capture Multiple Contexts (PyTorch)
(github.com/benedekrozemberczki)
3 points
benitorosenberg
6 years ago
discuss
235.
▲
Great tool to automate, control and reproduce Linux and OS X environments
(github.com/pearl-core)
3 points
sqoox
6 years ago
discuss
236.
▲
Reproducible Workflow with Guix, CWL and IPFS
(github.com/pjotrp)
3 points
freeduck
6 years ago
discuss
237.
▲
Unsupervised Cross-Lingual Representation Learning at Scale (XLM-RoBERTa)
(github.com/pytorch)
3 points
Anon84
6 years ago
discuss
238.
▲
HoloGAN: Unsupervised learning of 3D representations from natural images
(github.com/thunguyenphuoc)
3 points
bryanrasmussen
7 years ago
discuss
239.
▲
Adversarial Fisher Vectors for Unsupervised Representation Learning
(github.com/apple)
3 points
gok
7 years ago
discuss
240.
▲
AmpliGraph: Python Library for Representation Learning on Knowledge Graphs
(github.com/Accenture)
3 points
mpweiher
7 years ago
discuss
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