# Low-resource Adaptation

Q3-30b-A3b-Pentiment is a large language model based on the LLaMA architecture, optimized through quantization for various text generation tasks.

PEGASUS-XSum is a pre-trained text summarization model based on the PEGASUS architecture, specifically optimized for extreme summarization (XSum) tasks.

This is a model based on the Hugging Face Transformers library, optimized using Unsloth. Specific functionalities and use cases require further information.

This model is based on the transformers library, and its specific purpose and functionality require further information to determine.

A text summarization model trained based on the mt5-base architecture, capable of extracting key information from text to generate summaries.

A video understanding model fine-tuned based on MCG-NJU/videomae-base, with average performance on the evaluation set (accuracy 50%)

This is a multimodal model based on the Llama architecture, supporting vision and text instructions, optimized with 4-bit quantization.

A model fine-tuned based on bert-base-uncased for textual entailment recognition tasks, with an accuracy of 66.43%

Kok-Base is a multilingual model supporting English, Arabic, and Czech, suitable for various natural language processing tasks.

This is a transformers model hosted on Hugging Face Hub, with specific functions and purposes not clearly stated.

DeepSeek-R1-Distill-Qwen-32B-abliterated is a distilled version based on Qwen-32B, offering multiple quantization options to accommodate different hardware requirements.

This is a transformers model hosted on Hugging Face Hub. Specific functions and usage require further information.

A multimodal language model based on the Llama-3 architecture, natively supporting audio and text input comprehension, focusing on enhancing large language models' understanding of audio.

A Meta LLaMA-3 70B-based instruction-tuned model, quantized for local deployment and efficient inference.

Based on the Mistral 7B large language model, fine-tuned through pre-trained model merging on the Date-DPO-v2 dataset, excelling in role-playing, creative writing, and general intelligent tasks.

A large language model fine-tuned on the ultrachat_200k dataset based on microsoft/phi-2, suitable for dialogue generation tasks.

Mamba is an efficient language model based on the State Space Model (SSM) architecture, with 1.4B parameters, supporting text generation tasks

Re-uploaded version of Microsoft's multilingual MiniLM v2 model, optimized for use with the HuggingFace transformers library

LLaVA-JP is a Japanese visual language model capable of engaging in dialogue about input images, fine-tuned from llm-jp-1.3b-v1.0 using the LLaVA method.

A language model fine-tuned on the wikitext2 dataset based on the GPT-2 architecture

A large language model fine-tuned based on MythoMax-L2-13b, optimized through LoRA technology merging, suitable for creative text generation and dialogue tasks

Chinese to English translation model fine-tuned based on Helsinki-NLP/opus-mt-zh-en

A Korean-English translation model fine-tuned based on Helsinki-NLP's opus-mt-ko-en model

A chat model developed based on TimDettmers' Guanaco 13b qLoRa technology, suitable for dialogue generation tasks.

A Q&A model fine-tuned based on hfl/chinese-pert-large, suitable for Chinese Q&A tasks

A model fine-tuned based on deepset/roberta-base-squad2, specific purpose not explicitly stated

This model is a fine-tuned version of distilbert-base-uncased on the becasv3 dataset, primarily used for text generation tasks.

This model is a fine-tuned version of distilbert-base-uncased on the becasv2 dataset, primarily used for text classification tasks.

A fine-tuned version of the distilbert-base-uncased model on the becasv2 dataset, primarily used for text-related tasks.

This model is a fine-tuned version of distilbert-base-uncased on the becasv2 dataset, primarily used for text classification or related tasks.

Speech recognition model fine-tuned based on facebook/wav2vec2-large-960h-lv60-self

A fine-tuned model based on distilroberta-base, suitable for specific NLP tasks

A fine-tuned version based on the distilroberta-base model, suitable for text-related tasks

A model fine-tuned based on bert-base-uncased, primarily used for fill-in-the-blank tasks

A speech recognition model fine-tuned on a random noise dataset based on the facebook/wav2vec2-base model

A model fine-tuned based on distilbert-base-uncased, with specific task and dataset information not provided

This model is a fine-tuned audio classification model based on distilhubert trained on a common language dataset, primarily used for language recognition tasks.

An automatic speech recognition (ASR) solution combining the pyctcdecode library with Hugging Face models, providing efficient decoding capabilities

A text classification model fine-tuned on the GLUE RTE task based on the BERT base model

A versatile language model based on Transformer architecture, supporting tasks such as text generation, Q&A, and code completion