Hugging Face model: tensorblock/LDCC_LoRA_full-GGUF
Author: tensorblock
Created: 2024-12-14 20:19:43
Last modified: 2026-01-27 20:11:59
Pipeline: text-generation
Library: transformers
Likes: 0 | Downloads: 25
Tags: transformers, gguf, TensorBlock, GGUF, text-generation, ko, dataset:cong1230/Mental_illness_chatbot_training_dataset, base_model:cong1230/LDCC_LoRA_full, base_model:quantized:cong1230/LDCC_LoRA_full, license:mit, endpoints_compatible, region:us
Base model relation: quantized
Base models: id: cong1230/LDCC_LoRA_full
Card metadata:
license: mit
datasets: cong1230/Mental_illness_chatbot_training_dataset
language: ko
library_name: transformers
pipeline_tag: text-generation
description: Model Purpose and Target Domain:
This model is designed for text generation, specifically for the domain of mental health counseling chatbots. Its aim is to provide support for various mental health issues through conversations with users.

Unique Features and Capabilities:
The model specializes in mental health counseling, generating responses based on users' text inputs, performing sentiment analysis, and providing appropriate counseling. It also incorporates knowledge about various mental health-related topics to offer more effective counseling.

Performance Metrics and Benchmarks:
Specific information about performance metrics and benchmarks is not currently available. The quantitative performance of the model needs to be evaluated in real-world usage scenarios.

Training Procedure and Techniques:
The model was fine-tuned using the Peft library with Low-Rank Adaptation (LoRA) technique. This approach allows the model to effectively learn and apply knowledge and language specific to mental health counseling in chatbot interactions.
tags: TensorBlock, GGUF
base_model: cong1230/LDCC_LoRA_full