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meta-llama-3.1-8b-instruct
The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.
Model developer: Meta
Model Architecture: Llama 3.1 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: llama3.1
meta-llama-3.1-70b-instruct
The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.
Model developer: Meta
Model Architecture: Llama 3.1 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: llama3.1
meta-llama-3.1-8b-instruct:grammar-functioncall
This is the standard Llama 3.1 8B Instruct model with grammar and function call enabled.
When grammars are enabled in LocalAI, the LLM is forced to output valid tools constrained by BNF grammars. This can be useful for ensuring that the model outputs are valid and can be used in a production environment.
For more information on how to use grammars in LocalAI, see https://localai.io/features/openai-functions/#advanced and https://localai.io/features/constrained_grammars/.
Repository: localaiLicense: llama3.1
meta-llama-3.1-8b-instruct:Q8_grammar-functioncall
This is the standard Llama 3.1 8B Instruct model with grammar and function call enabled.
When grammars are enabled in LocalAI, the LLM is forced to output valid tools constrained by BNF grammars. This can be useful for ensuring that the model outputs are valid and can be used in a production environment.
For more information on how to use grammars in LocalAI, see https://localai.io/features/openai-functions/#advanced and https://localai.io/features/constrained_grammars/.
Repository: localaiLicense: llama3.1
meta-llama-3.1-8b-claude-imat
Meta-Llama-3.1-8B-Claude-iMat-GGUF: Quantized from Meta-Llama-3.1-8B-Claude fp16. Weighted quantizations were creating using fp16 GGUF and groups_merged.txt in 88 chunks and n_ctx=512. Static fp16 will also be included in repo. For a brief rundown of iMatrix quant performance, please see this PR. All quants are verified working prior to uploading to repo for your safety and convenience.
Repository: localaiLicense: llama3.1
meta-llama-3.1-8b-instruct-abliterated
This is an uncensored version of Llama 3.1 8B Instruct created with abliteration.
Repository: localaiLicense: llama3.1
llama-3.1-70b-japanese-instruct-2407
The Llama-3.1-70B-Japanese-Instruct-2407-gguf model is a Japanese language model that uses the Instruct prompt tuning method. It is based on the LLaMa-3.1-70B model and has been fine-tuned on the imatrix dataset for Japanese. The model is trained to generate informative and coherent responses to given instructions or prompts. It is available in the gguf format and can be used for a variety of tasks such as question answering, text generation, and more.
Repository: localaiLicense: llama3.1
openbuddy-llama3.1-8b-v22.1-131k
OpenBuddy - Open Multilingual Chatbot
Repository: localaiLicense: llama3.1
llama3.1-8b-fireplace2
Fireplace 2 is a chat model, adding helpful structured outputs to Llama 3.1 8b Instruct.
an expansion pack of supplementary outputs - request them at will within your chat:
Inline function calls
SQL queries
JSON objects
Data visualization with matplotlib
Mix normal chat and structured outputs within the same conversation.
Fireplace 2 supplements the existing strengths of Llama 3.1, providing inline capabilities within the Llama 3 Instruct format.
Version
This is the 2024-07-23 release of Fireplace 2 for Llama 3.1 8b.
We're excited to bring further upgrades and releases to Fireplace 2 in the future.
Help us and recommend Fireplace 2 to your friends!
Repository: localaiLicense: llama3.1
sekhmet_aleph-l3.1-8b-v0.1-i1
The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.
Model developer: Meta
Model Architecture: Llama 3.1 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: llama3.1
l3.1-8b-llamoutcast-i1
Warning: this model is utterly cursed.
Llamoutcast
This model was originally intended to be a DADA finetune of Llama-3.1-8B-Instruct but the results were unsatisfactory. So it received some additional finetuning on a rawtext dataset and now it is utterly cursed.
It responds to Llama-3 Instruct formatting.
Repository: localaiLicense: cc-by-nc-4.0
genius-llama3.1-i1
Finetuned Llama-3.1 base on Lex Fridman's podcast transcript.
Repository: localaiLicense: llama3.1
llama3.1-8b-chinese-chat
llama3.1-8B-Chinese-Chat is an instruction-tuned language model for Chinese & English users with various abilities such as roleplaying & tool-using built upon the Meta-Llama-3.1-8B-Instruct model. Developers: [Shenzhi Wang](https://shenzhi-wang.netlify.app)*, [Yaowei Zheng](https://github.com/hiyouga)*, Guoyin Wang (in.ai), Shiji Song, Gao Huang. (*: Equal Contribution) - License: [Llama-3.1 License](https://huggingface.co/meta-llama/Meta-Llla...
m-3.1-8B/blob/main/LICENSE) - Base Model: Meta-Llama-3.1-8B-Instruct - Model Size: 8.03B - Context length: 128K(reported by [Meta-Llama-3.1-8B-Instruct model](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct), untested for our Chinese model)
Repository: localaiLicense: llama3.1
llama3.1-70b-chinese-chat
"Llama3.1-70B-Chinese-Chat" is a 70-billion parameter large language model pre-trained on a large corpus of Chinese text data. It is designed for chat and dialog applications, and can generate human-like responses to various prompts and inputs. The model is based on the Llama3.1 architecture and has been fine-tuned for Chinese language understanding and generation. It can be used for a wide range of natural language processing tasks, including language translation, text summarization, question answering, and more.
Repository: localaiLicense: llama3.1
llama-3.1-techne-rp-8b-v1
athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit was further trained in the order below:
SFT
Doctor-Shotgun/no-robots-sharegpt
grimulkan/LimaRP-augmented
Inv/c2-logs-cleaned-deslopped
DPO
jondurbin/truthy-dpo-v0.1
Undi95/Weyaxi-humanish-dpo-project-noemoji
athirdpath/DPO_Pairs-Roleplay-Llama3-NSFW
Repository: localaiLicense: llama3.1
llama-spark
Llama-Spark is a powerful conversational AI model developed by Arcee.ai. It's built on the foundation of Llama-3.1-8B and merges the power of our Tome Dataset with Llama-3.1-8B-Instruct, resulting in a remarkable conversationalist that punches well above its 8B parameter weight class.
Repository: localaiLicense: llama3
l3.1-70b-glitz-v0.2-i1
this is an experimental l3.1 70b finetuning run... that crashed midway through. however, the results are still interesting, so i wanted to publish them :3
Repository: localaiLicense: llama3.1
calme-2.3-legalkit-8b-i1
This model is an advanced iteration of the powerful meta-llama/Meta-Llama-3.1-8B-Instruct, specifically fine-tuned to enhance its capabilities in the legal domain. The fine-tuning process utilized a synthetically generated dataset derived from the French LegalKit, a comprehensive legal language resource.
To create this specialized dataset, I used the NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO model in conjunction with Hugging Face's Inference Endpoint. This approach allowed for the generation of high-quality, synthetic data that incorporates Chain of Thought (CoT) and advanced reasoning in its responses.
The resulting model combines the robust foundation of Llama-3.1-8B with tailored legal knowledge and enhanced reasoning capabilities. This makes it particularly well-suited for tasks requiring in-depth legal analysis, interpretation, and application of French legal concepts.
Repository: localaiLicense: llama3.1
fireball-llama-3.11-8b-v1orpo
Developed by: EpistemeAI
License: apache-2.0
Finetuned from model : unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit
Finetuned methods: DPO (Direct Preference Optimization) & ORPO (Odds Ratio Preference Optimization)
Repository: localaiLicense: apache-2.0
hubble-4b-v1
Equipped with his five senses, man explores the universe around him and calls the adventure 'Science'.
This is a finetune of Nvidia's Llama 3.1 4B Minitron - a shrunk down model of Llama 3.1 8B 128K.
Repository: localaiLicense: llama3.1
reflection-llama-3.1-70b
Reflection Llama-3.1 70B is (currently) the world's top open-source LLM, trained with a new technique called Reflection-Tuning that teaches a LLM to detect mistakes in its reasoning and correct course.
The model was trained on synthetic data generated by Glaive. If you're training a model, Glaive is incredible — use them.
Repository: localaiLicense: llama3.1
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