AI Dataset2022
Curated English Wikipedia text prepared for language-model training and evaluation, provided in WikiText-2 and WikiText-103 variants. Preserves original case, punctuation and numbers; offers raw and tokenized splits for long-range language modeling under a CC BY‑SA license.
AI Dataset2022
Provides cleaned, per-language snapshots of Wikipedia articles (id, url, title, text) packaged as Hugging Face dataset configs (Parquet). Covers 300+ language configs and dated dumps — useful for language modeling, multilingual NLP, retrieval, and RAG pipelines.
AI Model2022
Encodes sentences and short paragraphs into 384-dimensional semantic vectors for retrieval, clustering, and similarity tasks. Fine-tuned from MiniLM-L6-H384 on ~1.17B sentence pairs with a contrastive objective; defaults to 256 word-piece truncation.
AI Model2022
Autoregressive transformer that generates English text from a prompt and can be fine-tuned for downstream NLP tasks. This is the 124M-parameter GPT-2 checkpoint (causal LM, byte-level BPE, 1024-token context) hosted on Hugging Face.
AI Model2022
A compact pretrained bidirectional Transformer distilled from BERT base for masked language modeling and downstream NLP fine-tuning. Trained via knowledge distillation on BookCorpus and English Wikipedia, it reduces size/latency (≈67M params) while preserving BERT-like representations.
Made reinforcement learning from human feedback (RLHF) the standard alignment recipe: collect demonstrations and preference rankings, train a reward model, then optimize with PPO. A 1.3B aligned model was preferred over the 175B GPT-3 by human raters.
AI Dataset2022
Benchmark dataset of ~8.5k grade-school math word problems with step-by-step solutions and calculator annotations for evaluating multi-step arithmetic reasoning in language models. Provided in two configs (main and socratic) and commonly used for chain-of-thought prompting, fine-tuning, and verifier training.
A line-by-line PyTorch reimplementation of the Transformer paper as a runnable notebook, where each part of the paper sits next to the code that implements it — turning a dense architecture into something you can read and run end to end.
AI Model2022
Rust-and-Python toolkit that serves open-source LLMs (Llama, Falcon, Mixtral, StarCoder) over HTTP/gRPC with tensor parallelism, continuous batching, Flash/Paged Attention and quantization. Now in maintenance mode, pointing users toward vLLM and SGLang.
AI Dataset2022
Provides human preference comparison pairs and red-team conversation transcripts collected by Anthropic for training preference/reward models and studying harmful model behaviors; intended for RLHF and safety research, not for supervised fine-tuning of dialogue agents.
AI Dataset2022
Community-curated collection of ChatGPT-style prompts mirrored as a Hugging Face dataset; organized by task and model compatibility for quick reuse. Useful for prompt engineering, text-generation prototyping, and building conversational examples across multiple LLMs.
AI Train2022
Reproduces GPT-2 (124M) from scratch on OpenWebText in ~4 days on an 8xA100 node, with the whole stack kept to two ~300-line files: train.py for the loop and model.py for the architecture. A char-level Shakespeare run finishes in ~3 minutes on one GPU.