inference, language, library_name, pipeline_tag, tags, datasets

inference	language	library_name	pipeline_tag	tags	datasets
false	en	transformers	text-generation	llama	LDJnr/Capybara jondurbin/airoboros-3.2 unalignment/toxic-dpo-v0.1 LDJnr/Verified-Camel HuggingFaceH4/no_robots Doctor-Shotgun/no-robots-sharegpt Doctor-Shotgun/capybara-sharegpt

Norobara-ZLoss-8x7B

This is an instruct-tuned TinyLlama-1.1B-32k on several open-source instruct datasets, intended primarily for speculative decoding.

Usage:

The intended prompt format is a modified multi-turn Alpaca instruction format:

### Instruction:
{system prompt}

### Input:
{user message}

### Response:
{model response}

### Input:
{user message}

### Response:
{model response}

(etc.)

Bias, Risks, and Limitations

The model will show biases present in the base model. No ethical alignment was applied to prevent the generation of toxic or harmful outputs (in fact the opposite, with examples from toxic-DPO included), so generate at your own risk.

Training Details

This model was trained as a full finetune for 3 epochs using a single A100 GPU for around 3.5 hours.