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llama-3.2-1b-instruct:q4_k_m
The Meta Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. They outperform many of the available open source and closed chat models on common industry benchmarks.
Model Developer: Meta
Model Architecture: Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Repository: localaiLicense: llama3.2
llama-3.2-3b-instruct:q4_k_m
The Meta Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. They outperform many of the available open source and closed chat models on common industry benchmarks.
Model Developer: Meta
Model Architecture: Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Repository: localaiLicense: llama3.2
llama-3.2-3b-instruct:q8_0
The Meta Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. They outperform many of the available open source and closed chat models on common industry benchmarks.
Model Developer: Meta
Model Architecture: Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Repository: localaiLicense: llama3.2
llama-3.2-1b-instruct:q8_0
The Meta Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. They outperform many of the available open source and closed chat models on common industry benchmarks.
Model Developer: Meta
Model Architecture: Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Repository: localaiLicense: llama3.2
versatillama-llama-3.2-3b-instruct-abliterated
Small but Smart Fine-Tuned on Vast dataset of Conversations. Able to Generate Human like text with high performance within its size. It is Very Versatile when compared for it's size and Parameters and offers capability almost as good as Llama 3.1 8B Instruct.
Repository: localaiLicense: llama3.2
llama3.2-3b-enigma
Enigma is a code-instruct model built on Llama 3.2 3b. It is a high quality code instruct model with the Llama 3.2 Instruct chat format. The model is finetuned on synthetic code-instruct data generated with Llama 3.1 405b and supplemented with generalist synthetic data. It uses the Llama 3.2 Instruct prompt format.
Repository: localaiLicense: llama3.2
llama3.2-3b-esper2
Esper 2 is a DevOps and cloud architecture code specialist built on Llama 3.2 3b. It is an AI assistant focused on AWS, Azure, GCP, Terraform, Dockerfiles, pipelines, shell scripts and more, with real world problem solving and high quality code instruct performance within the Llama 3.2 Instruct chat format. Finetuned on synthetic DevOps-instruct and code-instruct data generated with Llama 3.1 405b and supplemented with generalist chat data.
Repository: localaiLicense: llama3.2
llama-3.2-3b-agent007
The model is a quantized version of EpistemeAI/Llama-3.2-3B-Agent007, developed by EpistemeAI and fine-tuned from unsloth/llama-3.2-3b-instruct-bnb-4bit. It was trained 2x faster with Unsloth and Huggingface's TRL library. Fine tuned with Agent datasets.
Repository: localaiLicense: llama3.2
llama-3.2-3b-agent007-coder
The Llama-3.2-3B-Agent007-Coder-GGUF is a quantized version of the EpistemeAI/Llama-3.2-3B-Agent007-Coder model, which is a fine-tuned version of the unsloth/llama-3.2-3b-instruct-bnb-4bit model. It is created using llama.cpp and trained with additional datasets such as the Agent dataset, Code Alpaca 20K, and magpie ultra 0.1. This model is optimized for multilingual dialogue use cases and agentic retrieval and summarization tasks. The model is available for commercial and research use in multiple languages and is best used with the transformers library.
Repository: localaiLicense: llama3.2
fireball-meta-llama-3.2-8b-instruct-agent-003-128k-code-dpo
The LLM model is a quantized version of EpistemeAI/Fireball-Meta-Llama-3.2-8B-Instruct-agent-003-128k-code-DPO, which is an experimental and revolutionary fine-tune with DPO dataset to allow LLama 3.1 8B to be an agentic coder. It has some built-in agent features such as search, calculator, and ReAct. Other noticeable features include self-learning using unsloth, RAG applications, and memory. The context window of the model is 128K. It can be integrated into projects using popular libraries like Transformers and vLLM. The model is suitable for use with Langchain or LLamaIndex. The model is developed by EpistemeAI and licensed under the Apache 2.0 license.
Repository: localaiLicense: llama3.2
llama-3.2-chibi-3b
Small parameter LLMs are ideal for navigating the complexities of the Japanese language, which involves multiple character systems like kanji, hiragana, and katakana, along with subtle social cues. Despite their smaller size, these models are capable of delivering highly accurate and context-aware results, making them perfect for use in environments where resources are constrained. Whether deployed on mobile devices with limited processing power or in edge computing scenarios where fast, real-time responses are needed, these models strike the perfect balance between performance and efficiency, without sacrificing quality or speed.
Repository: localaiLicense: llama3.2
llama-3.2-3b-reasoning-time
Lyte/Llama-3.2-3B-Reasoning-Time is a large language model with 3.2 billion parameters, designed for reasoning and time-based tasks in English. It is based on the Llama architecture and has been quantized using the GGUF format by mradermacher.
Repository: localaiLicense: llama3.2
llama-3.2-sun-2.5b-chat
Base Model
Llama 3.2 1B
Extended Size
1B to 2.5B parameters
Extension Method
Proprietary technique developed by MedIT Solutions
Fine-tuning
Open (or open subsets allowing for commercial use) open datasets from HF
Open (or open subsets allowing for commercial use) SFT datasets from HF
Training Status
Current version: chat-1.0.0
Key Features
Built on Llama 3.2 architecture
Expanded from 1B to 2.47B parameters
Optimized for open-ended conversations
Incorporates supervised fine-tuning for improved performance
Use Case
General conversation and task-oriented interactions
Repository: localaiLicense: llama3.2
llama-3.2-3b-instruct-uncensored
This is an uncensored version of the original Llama-3.2-3B-Instruct, created using mlabonne's script, which builds on FailSpy's notebook and the original work from Andy Arditi et al..
Repository: localaiLicense: llama3.2
calme-3.3-llamaloi-3b
This model is an advanced iteration of the powerful meta-llama/Llama-3.2-3B, specifically fine-tuned to enhance its capabilities in French Legal domain.
Repository: localaiLicense: llama3.2
calme-3.2-llamaloi-3b
This model is an advanced iteration of the powerful meta-llama/Llama-3.2-3B, specifically fine-tuned to enhance its capabilities in French Legal domain.
Repository: localaiLicense: llama3.2
calme-3.1-llamaloi-3b
This model is an advanced iteration of the powerful meta-llama/Llama-3.2-3B, specifically fine-tuned to enhance its capabilities in French Legal domain.
Repository: localaiLicense: llama3.2
llama3.2-3b-enigma
ValiantLabs/Llama3.2-3B-Enigma is an Enigma model built on Llama 3.2 3b. It is a high-quality code-instruct model with the Llama 3.2 Instruct chat format. The model is finetuned on synthetic code-instruct data generated using Llama 3.1 405b and supplemented with generalist synthetic data. This model is suitable for both code-instruct and general chat applications.
Repository: localaiLicense: llama3.2
llama3.2-3b-shiningvaliant2-i1
Shining Valiant 2 is a chat model built on Llama 3.2 3b, finetuned on our data for friendship, insight, knowledge and enthusiasm.
Finetuned on meta-llama/Llama-3.2-3B-Instruct for best available general performance
Trained on a variety of high quality data; focused on science, engineering, technical knowledge, and structured reasoning
Also available for Llama 3.1 70b and Llama 3.1 8b!
Version
This is the 2024-09-27 release of Shining Valiant 2 for Llama 3.2 3b.
Repository: localaiLicense: llama3.2
llama-doctor-3.2-3b-instruct
The Llama-Doctor-3.2-3B-Instruct model is designed for text generation tasks, particularly in contexts where instruction-following capabilities are needed. This model is a fine-tuned version of the base Llama-3.2-3B-Instruct model and is optimized for understanding and responding to user-provided instructions or prompts. The model has been trained on a specialized dataset, avaliev/chat_doctor, to enhance its performance in providing conversational or advisory responses, especially in medical or technical fields.
Repository: localaiLicense: llama3.2
onellm-doey-v1-llama-3.2-3b
This model is a fine-tuned version of LLaMA 3.2-3B, optimized using LoRA (Low-Rank Adaptation) on the NVIDIA ChatQA-Training-Data. It is tailored for conversational AI, question answering, and other instruction-following tasks, with support for sequences up to 1024 tokens.
Repository: localaiLicense: llama3.2
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