datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
llm-attacked-prompts-clm
LLM-Paraphrased Adversarial Prompts
LLM-paraphrased adversarial prompts for three code-generation benchmarks
(MBPP+, HumanEval+, CanItEdit), used by
RobustEval-CLM's
LLMParaphraseAttack.
Each row corresponds to one task in the source benchmark and carries the
original prompt alongside an adversarial rewrite produced by an LLM under a
BERTScore faithfulness constraint.
Configs
config
source benchmark
rewrite surface
mbpp
MBPP+
line 1 of the 4-line prompt… See the full description on the dataset page: https://huggingface.co/datasets/TheFatBlue/llm-attacked-prompts-clm.cl-macros-creative
cl-macros-creative
Hand-curated and LLM-brainstormed Common Lisp macro examples beyond what
j14i/cl-ds covers from
established libraries. Built as Phase-2 exploration corpus for
j14i/cl-macro-27b-lora.
Schema
Mirrors j14i/cl-ds:
field
meaning
instruction
natural-language description of the macro
input
sample call form
output
the reference (defmacro ...) source
macroexpand
exact result of (macroexpand-1 input) under that defmacro
category
control-flow /… See the full description on the dataset page: https://huggingface.co/datasets/j14i/cl-macros-creative.cl-macros-thinking-clean
cl-macros-thinking
Chat-format Common Lisp macro dataset enriched with <think>...</think>
reasoning traces. Each row is a single training example:
{
"messages": [
{"role": "system", "content": "You are an expert Common Lisp macro programmer..."},
{"role": "user", "content": "Write a Common Lisp macro to handle ..."},
{"role": "assistant", "content": "<think>...reasoning...</think>\n\n(defmacro ...)"}
]
}
Splits
split
rows
train
1607… See the full description on the dataset page: https://huggingface.co/datasets/j14i/cl-macros-thinking-clean.cl-macros-thinking
cl-macros-thinking
Chat-format Common Lisp macro dataset enriched with <think>...</think>
reasoning traces. Each row is a single training example:
{
"messages": [
{"role": "system", "content": "You are an expert Common Lisp macro programmer..."},
{"role": "user", "content": "Write a Common Lisp macro to handle ..."},
{"role": "assistant", "content": "<think>...reasoning...</think>\n\n(defmacro ...)"}
]
}
Splits
split
rows
train
1828… See the full description on the dataset page: https://huggingface.co/datasets/j14i/cl-macros-thinking.