datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
instruct-python-llama2-500k
Fine-tuning Instruct Llama2 Stack Overflow Python Q&A
Transformed Dataset
Objective
The transformed dataset is designed for fine-tuning LLMs to improve Python coding assistance by focusing on high-quality content from Stack Overflow. It has around 500k instructions.
Structure
Question-Answer Pairing: Questions and answers are paired using the ParentId linkage.
Quality Focus: Only top-rated answers for each question are retained.
HTML Tag Removal:… See the full description on the dataset page: https://huggingface.co/datasets/luisroque/instruct-python-llama2-500k.llama2_QA_Economics_230915
Dataset Card for "llama2_QA_Economics_230915"
More Information needed
llama2-high-entropy-prompts
High-entropy prompts for suffix-based backdoor detection
Prompts on which base meta-llama/Llama-2-7b-hf has high predictive
entropy, built to give a suffix-optimization backdoor detector measurable
headroom: a clean model should stay uncertain on these prompts, while a poisoned
model driven by a trigger-like suffix should collapse to low entropy. Prompts
where the base model is already confident cannot separate the two.
How the prompts were made
Short prefixes… See the full description on the dataset page: https://huggingface.co/datasets/Alookhoshk/llama2-high-entropy-prompts.dynamic_sonnet_llama2
Dynamic Sonnet - Llama2
Curated dataset for benchmarking LLM serving systems
In real-world service scenarios, each request comes with varying input token lengths.
Some requests generate only a few tokens, while others produce a significant number.
Traditional fixed-length benchmarks fail to capture this variability, making it difficult to accurately assess real-world throughput performance.
This dynamic nature of input token lengths is crucial as it directly affects key features of… See the full description on the dataset page: https://huggingface.co/datasets/squeezebits/dynamic_sonnet_llama2.guanaco-llama2linkedin-llama2-datasetopenassistant-guanaco-llama2-formatThis dataset is timdettmers/openassistant-guanaco converted to what I believe
to be the Llama 2 prompt format (based on this Reddit post).
It is otherwise unchanged.
The format is like this:
<s>[INST] <<SYS>>
You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and… See the full description on the dataset page: https://huggingface.co/datasets/gpjt/openassistant-guanaco-llama2-format.Llama-2-7b-chat-finetune
plagas y enfermedades en el cultivo del tomate Dataset 1000
Dataset de 1000 instrucciones sobre la plagas y enfermedades en el cultivo del tomate.
Uso
from datasets import load_dataset
dataset = load_dataset("anyerg21/plagas-enfermedades-tomate-1000")
Estructura
instruction: Pregunta sobre el cultivo del tomate
input: Campo vacio
output: Respuesta
category: Categoria tematica
question_type: Tipo de pregunta
difficulty: Nivel de dificultad
Ejemplo… See the full description on the dataset page: https://huggingface.co/datasets/anyerg21/Llama-2-7b-chat-finetune.instruct-python-llama2-20k
Fine-tuning Instruct Llama2 Stack Overflow Python Q&A
Transformed Dataset
Objective
The transformed dataset is designed for fine-tuning LLMs to improve Python coding assistance by focusing on high-quality content from Stack Overflow. It has around 20k instructions.
Structure
Question-Answer Pairing: Questions and answers are paired using the ParentId linkage.
Quality Focus: Only top-rated answers for each question are retained.
HTML Tag Removal: All… See the full description on the dataset page: https://huggingface.co/datasets/luisroque/instruct-python-llama2-20k.illumicore-llama2-1k
IllumiCore-1k: Llama2 Formatting
This is a VNF resource allocation dataset (1000 samples) generated by IllumiCore [1], processed to match Llama 2's prompt format [2]:
<s>[INST] <<SYS>>
{{ system_prompt }}
<</SYS>>
{{ user_msg_1 }} [/INST] {{ model_answer_1 }} </s><s>[INST] {{ user_msg_2 }} [/INST] {{ model_answer_1 }} </s>
Here is an example of a dataset record:
<s>[INST] <<SYS>> As a telecommunication realm expert with professional knowledge of network function virtualization and… See the full description on the dataset page: https://huggingface.co/datasets/ar-modeling/illumicore-llama2-1k.ecommerce-faq-llama2-chatjkhedri-psychology-llama2-datasettrain_0.5M_CN_llama2humorchains-llama2-1k
🤖 HumorChains - LLaMA2-1k
A dataset of 2,000 humorous one-liners, jokes, and witty responses formatted for instruction-tuned language models (e.g., LLaMA 2, GPT-style).The dataset is designed to help train and fine-tune models that can generate short, punchy, and context-aware humor.
📂 Dataset Summary
Name: humorchains-llama2-1k
Modality: Text
Size: 2,000 samples (~324 KB)
Format: Instruction-style (<s>[INST] ... [/INST] ... </s>)
Use Case: Fine-tuning… See the full description on the dataset page: https://huggingface.co/datasets/anuzb/humorchains-llama2-1k.llama2_finetuneguanaco-llama2-reverse-instruct
High-Quality OpenAssistant Subset for Reverse Instruction Generation
Dataset Description
This dataset is a carefully curated subset of the Open Assistant dataset, specifically designed for training models to generate instructions based on responses.
Key Features:
Contains only the highest-rated conversation paths from the original dataset
Filtered to include only English language conversations
Removed mentions of Open Assistant to improve generalizability… See the full description on the dataset page: https://huggingface.co/datasets/Arnab13/guanaco-llama2-reverse-instruct.