Phase 1 — Boot & Baselines (1–5) 1. autotrain-Llama2chat Why: gentle on-ramp to chat fine-tunes. Do: run inference, inspect tokenizer, export to GGUF. 2. NousResearch-Llama2-chat Why: compare a known chat baseline. Do: side-by-side eval vs #1 (accuracy, toxicity, latency). 3. NousResearch-Llama2-7bhf Why: plain 7B base; learn prompting vs. instruction. Do: simple domain prompts; log failure…
Tag: huggingface
21 Models for AI Reskilling
Why having 21 models under your Hugging Face Org (like InnerI) is more powerful for reskilling than a paper certificate. I. Why 21 Models Matter • Each model = a practical proof of skill. • Covers different layers of reskilling (chat, embeddings, classification, fine-tunes, LoRA adapters, RAG pipelines). • Shows I can ship — not…
synCAI-144k-llama3 (model) fine-tuned on synCAI_144kda (dataset)
synCAI144kda is a Synthetic Consciousness Artificial Intelligence dataset containing 144,001 data rows designed to advance AI and consciousness studies. It includes 10,000 original rows with diverse questions and responses, as well as 144,000 synthetic rows from Mostly AI, totaling 3,024,000 individual datapoints. This comprehensive dataset is ideal for training AI models, exploring consciousness topics, and…
Inner I Net Company/ - Innovative Solutions to Shape Reality 