Platypus 30B AWQ is an open-source language model by TheBloke. Features: 30b LLM, VRAM: 17.6GB, Context: 2K, License: other, Quantized, LLM Explorer Score: 0.09.
AI research, instructional content, automated text generation
Primary Use Cases:
text completion, question-answering, language understanding
Considerations:
Not suitable as a substitute for human judgment.
Additional Notes
Platypus-30B is available in a quantized AWQ format for efficient inference, allowing use on smaller GPUs which can lead to cost savings.
Supported Languages
English (Proficient)
Training Details
Data Sources:
dataset of highly filtered and curated question and answer pairs
Methodology:
instruction fine-tuning with LoRA
Hardware Used:
4 A100 80GB GPUs
Model Architecture:
Auto-regressive language model based on the LLaMA transformer architecture
Input Output
Input Format:
Formatted prompts using instruction template. Example: 'Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {prompt} ### Response:'
Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Platypus-30B-AWQ.
Rank the Platypus 30B AWQ Capabilities
๐ Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! ๐
Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation
What open-source LLMs or SLMs are you in search of? 52758 in total.