language-model
languagemodelBabyLM-130M-ilm_it-ilm_pl-tokenizer_ilm_bilingual_it_pl_bpe_trailing_ws_32000Untangling-Multi-Concern-Commits-with-Small-Language-Models-GGUFrecursive-language-model-198mBaize-Traditional-Chinese-Medicine-Large-Language-Model-GGUFBabyLM-130M-ilm_eu-tokenizer_ilm_mono_eu_bpe_32000BabyLM-130M-ilm_it-ilm_pl-tokenizer_ilm_bilingual_it_pl_unigram_32000BabyLM-130M-ilm_es-tokenizer_ilm_mono_es_bpe_32000
pal-resultscis5300-language-models
CIS 5300 Language Models Dataset
Dataset for Homework 3 of CIS 5300 (Natural Language Processing) at Penn.
Cities config
Country-of-origin classification over short city-name strings, drawn from
nine countries (Afghanistan, China, Germany, Finland, France, India, Iran,
Pakistan, South Africa).
from datasets import load_dataset
cities = load_dataset("CCB/cis5300-language-models", "cities")
Split
Rows
Has labels?
train
12,392
yes
validation
1,548
yes
test
1… See the full description on the dataset page: https://huggingface.co/datasets/CCB/cis5300-language-models.nepalitext-language-model-dataset
Dataset Card for "nepalitext-language-model-dataset"
Dataset Summary
"NepaliText" language modeling dataset is a collection of over 13 million Nepali text sequences (phrases/sentences/paragraphs) extracted by combining the datasets: OSCAR , cc100 and a set of scraped Nepali articles on Wikipedia.
Supported Tasks and Leaderboards
This dataset is intended to pre-train language models and word representations on Nepali Language.
Languages
The data is… See the full description on the dataset page: https://huggingface.co/datasets/Sakonii/nepalitext-language-model-dataset.core-language-model-data
Core Language Model
A small coding + general-purpose language model built from scratch in pure NumPy — no PyTorch, no JAX, no autograd library. Every piece (autograd engine, tokenizer, attention, layer norm) is hand-written and gradient-checked.
This is a from-first-principles build of a transformer language model, aimed at understanding every formula well enough to reimplement it without reference.
Why pure NumPy?
The goal isn't a competitive model — it's a fully… See the full description on the dataset page: https://huggingface.co/datasets/karthik-2905/core-language-model-data.Anthropic_HH_Golden
Dataset Card for Anthropic_HH_Golden
This dataset is constructed to test the ULMA technique as mentioned in the paper Unified Language Model Alignment with Demonstration and Point-wise Human Preference (under review, and an arxiv link will be provided soon). They show that replacing the positive samples in a preference dataset by high-quality demonstration data (golden data) greatly improves the performance of various alignment methods (RLHF, DPO, ULMA). In particular, the ULMA… See the full description on the dataset page: https://huggingface.co/datasets/Unified-Language-Model-Alignment/Anthropic_HH_Golden.language_model_fr