datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
LLM-self-identification Self Identification – Give your Language model an identity
About Self Identification
Self identification is training set SupraLabs curated for developers/trainers to experiment with to let your language model know about their identity.
Self identification let your LM know these information about them:
Model ID
Model Name
Model Description
Model Creator
Model Family
Model Architecture
Parameter Count
Knowledge Cutoff
Here is an example from the dataset:
If… See the full description on the dataset page: https://huggingface.co/datasets/SupraLabs/LLM-self-identification.LLM-self-identification
LLM Identity · Give your LLM an identity
Self Identification
The Self-Identification Dataset, curated by Qyrou, is a specialized training resource designed to help developers and trainers establish clear self-identity awareness within language models. By incorporating this dataset, models can accurately learn and convey essential metadata about themselves, including their Model ID, Model Name, Model Description, Model Creator, Model Family, Model Architecture, Parameter Count… See the full description on the dataset page: https://huggingface.co/datasets/Qyrou/LLM-self-identification.Vertex-0.6-35M-self-identification
Vertex 0.6 35M — Self Identification
A self-identification SFT dataset for Vertex-0.6-35M-Instruct:
459 ChatML-style conversations that teach the model who it is — its name,
creator, family, architecture, parameter count, and knowledge cutoff.
Made from SupraLabs/LLM-self-identification
(Apache-2.0), with every {{SELF_ID.*}} marker replaced with the Vertex 0.6
35M identity:
Marker
Value
MODEL_ID
VertexResearch/Vertex-0.6-35M-Instruct
MODEL_NAME
Vertex 0.6 35M… See the full description on the dataset page: https://huggingface.co/datasets/VertexResearch/Vertex-0.6-35M-self-identification.lmsys-self-identificationlmsys-self-identification-new