bluuwhale/L3-SAO-MIX-8B-V1
!Bluuwhale(https://huggingface.co/bluuwhale/test1/resolve/main/bluuwhale.png) Experimental merge of Sao10k(https://huggingface.co/Sao10K) Llama3-8B based model L3-SAO-MIX-8B-V1 This is a merge of pre-trained language models created using mergekit(htt...
Thành tựu nổi bật
Những danh hiệu mới nhất của dự án
#1 Repository Của Tuần
#1 Repository Của Tuần
#1 Repository Của Tuần
Experimental merge of Sao10k Llama3-8B based model
L3-SAO-MIX-8B-V1
This is a merge of pre-trained language models created using mergekit.
I'm trying to combine the best model from Sao10k. And turn out, this is beyond my expectation. I use it for RP and ERP on scenario card. And it follow the instruction very well (At least for me). All credits and thanks go to Sao10k for providing amazing models used in the merge.
Prompt template: Llama3 Instruct.
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
{input}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
{output}<|eot_id|>
Settings
Temprature: 1.3
Min-P: 0.1
// If using DRY
Multiplier: 2
Base: 1.75
Allowed Length: 2
Penalty Range: 0
Merge details
Merge Method
This model was merged using the della merge method using Sao10K/L3-8B-Niitama-v1 as a base.
Models Merged
The following models were included in the merge:
- Sao10K/L3-8B-Lunaris-v1
- Sao10K/L3-8B-Stheno-v3.2
- Sao10K/L3-8B-Niitama-v1
- Sao10K/L3-8B-Tamamo-v1
Configuration
The following YAML configuration was used to produce this model:
base_model: Sao10K/L3-8B-Niitama-v1
merge_method: della
dtype: bfloat16
models:
- model: Sao10K/L3-8B-Lunaris-v1
parameters:
weight: 1.0
- model: Sao10K/L3-8B-Stheno-v3.2
parameters:
weight: 1.0
- model: Sao10K/L3-8B-Niitama-v1
parameters:
weight: 1.0
- model: Sao10K/L3-8B-Tamamo-v1
parameters:
weight: 1.0
Similar Projects
Discover other similar projects and AI models.
Model Information 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 onl...
Model Details Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dia...
DeepSeek-R1 Paper Link👁️ 1. Introduction We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT) as a p...
Model Details Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dia...
Qwen3-0.6B Qwen3 Highlights Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancement...
Llama 2 Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the repository for the 7B fine-tuned model, optimized for dialogue use cases and converted for the...
GPT-2 Test the whole generation capabilities here: https://transformer.huggingface.co/doc/gpt2-large Pretrained model on English language using a causal language modeling (CLM) objective. It was introduced in this paper(https://d4mucfpksywv.cloudfro...
Try gpt-oss · Guides · Model card · OpenAI blog Welcome to the gpt-oss series, OpenAI’s open-weight models(https://openai.com/open-models) designed for powerful reasoning, agentic tasks, and versatile developer use cases. We’re releasing two flavors...
Try gpt-oss · Guides · Model card · OpenAI blog Welcome to the gpt-oss series, OpenAI’s open-weight models(https://openai.com/open-models) designed for powerful reasoning, agentic tasks, and versatile developer use cases. We’re releasing two flavors...