Model Card for Wabisabi-v1.0

The Mistral-7B--based Large Language Model (LLM) is an noveldataset fine-tuned version of the Mistral-7B-v0.1

wabisabi has the following changes compared to Mistral-7B-v0.1.

  • 128k context window (8k context in v0.1)
  • Achieving both high quality Japanese and English generation
  • Can be generated NSFW
  • Memory ability that does not forget even after long-context generation

This model was created with the help of GPUs from the first LocalAI hackathon.

We would like to take this opportunity to thank

List of Creation Methods

  • Chatvector for multiple models
  • Simple linear merging of result models
  • Domain and Sentence Enhancement with LORA
  • Context expansion

Instruction format

Vicuna-v1.1

Other points to keep in mind

  • The training data may be biased. Be careful with the generated sentences.
  • Memory usage may be large for long inferences.
  • If possible, we recommend inferring with llamacpp rather than Transformers.
Downloads last month
9
Safetensors
Model size
7.24B params
Tensor type
BF16
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Local-Novel-LLM-project/WabiSabi-V1

Quantizations
2 models