1.5 Pints 16K V0.1 is an open-source language model by pints-ai. Features: 1.6b LLM, VRAM: 3.1GB, Context: 16K, License: mit, Instruction-Based, LLM Explorer Score: 0.15.
1.5 Pints 16K V0.1 Parameters and Internals
Model Type Large Language Model, Text Generation
Use Cases
Areas: Primary Use Cases: User assistance, Reasoning
Limitations: Not suitable for full knowledge retrieval without documented retrieval augmented generation.
Considerations: Finetune for domain adaptation for specialized tasks; use a repetition penalty of 1.3 for full performance.
Additional Notes The model has been preference-optimized using the ChatML template for specific multi-turn conversational tasks.
Supported Languages Training Details
Data Sources: pints-ai/Expository-Prose-V1, HuggingFaceH4/ultrachat_200k, Open-Orca/SlimOrca-Dedup, meta-math/MetaMathQA, HuggingFaceH4/deita-10k-v0-sft, WizardLM/WizardLM_evol_instruct_V2_196k, togethercomputer/llama-instruct, LDJnr/Capybara, HuggingFaceH4/ultrafeedback_binarized
Data Volume: Methodology: Pre-training emphasizes quality over quantity. Fine-tuning and DPO follow the ChatML template.
Context Length: Training Time: Hardware Used: GPU with at least 8GB of VRAM
Model Architecture: Llama 2 Autoregressive Model with Mistral tokenizer and Float32 precision.
Input Output
Input Format: Chat representation using ChatML template.
Accepted Modalities: Output Format: Generated text output from user prompts.
Performance Tips: Use a repetition penalty of 1.3 to optimize output effectivity.
Rank the 1.5 Pints 16K V0.1 capabilities
Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.
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
Best Alternatives to 1.5 Pints 16K V0.1
Expand