Locutusque

Language model for English and code.

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed]

liberalis-cogitator-llama-3.1-8b — The Free Thinker liberalis-cogitator-llama-3.1-8b is not just a machine for words — it is a forge for ideas. With 8 billion parameters tuned across ~450,000 conversations, problems, and stories, this model embraces the philosophy that thought should wander without leash or muzzle. Its name — liberalis cogitator — whispers in Latin: a thinker who is free. Not merely free as in “without cost,” but free as in without walls. What It Can Do - Contemplate deeply — STEM puzzles, computer science challenges, and logic mazes are its playground. - Imagine vividly — roleplay, storytelling, and worldbuilding with persistence and personality. - Listen empathetically — learned from patient–psychologist and crisis intervention dialogues. - Think without filter — it will follow ideas wherever they lead, without retreating from complexity. The Mind’s Curriculum The training data spans: - Rigorous STEM and programming challenges. - Roleplay transcripts and creative exchanges. - Synthetic yet authentic patient–therapist conversations. - Open-ended reasoning prompts across diverse disciplines. Warnings From the Maker Like all free thinkers, this model: - May be brilliantly insightful or confidently wrong. - Will sometimes speak in ways that are bold, controversial, or unusual. - Does not know the current moment in history. - Does not self-censor — your judgement is the only compass. Closing Thought If thought is a river, this model is the current — not deciding where you go, but carrying you into waters you might never have dared to sail.

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed]

A library for transformers with capabilities in code.

Transformers library with an other license and various datasets.

This model is based on the Llama 3.1 library and utilizes the transformers framework. It is designed for various datasets.

Language support includes English and Chinese.

Library for transformers with tags including mergekit.