·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
America needs to stop getting shocked by Chinese AI2h◆Advancing next-gen AI with materials science innovation2h◆Gritt exits stealth with $34 million for robots to build solar plants—then, everything else3h◆Capacity and Redundancy Trade-offs in Multi-Task Learning9h◆Predictive Training with Latent Imagination for Visual Quadruped Navigation9h◆Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making9h◆Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection9h◆Supervised Reward Inference9h◆PPO-HSC: An Exploratory Reinforcement Learning Framework Based on Wide-Area Policy Coverage Optimization9h◆Is Progressive Disclosure All You Need for Long-Context Agents?9h◆It Depends on the Dataset: When a Brain-Encoding Model's Predicted Responses Beat Their Visual Backbone for Video Memorability9h◆DMFNet: Dual-Backbone Multiscale Fusion Network for Urban Scene Classification9h◆Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration9h◆Time-Frequency Consistency Learning for Robust Speech Deepfake Detection9h◆Scientific reasoning does not reliably translate into scientific forecasting in frontier AI9h◆Language Triggers Hijack Language Circuits: A Mechanistic Analysis of Backdoor Behaviors in Large Language Models9h◆Kernel Regression with Tensor Trains and Hadamard Overparameterization9h◆AI-Augmented Human Resource Management? Insights from German companies9h◆Diagnosing Correctness Probes under Self-Judgement Confounding9h◆BLAD: A Historically Contextualized, Multilingual Dataset of Bangladeshi Legal Acts (1799 to 2025)9h◆America needs to stop getting shocked by Chinese AI2h◆Advancing next-gen AI with materials science innovation2h◆Gritt exits stealth with $34 million for robots to build solar plants—then, everything else3h◆Capacity and Redundancy Trade-offs in Multi-Task Learning9h◆Predictive Training with Latent Imagination for Visual Quadruped Navigation9h◆Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making9h◆Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection9h◆Supervised Reward Inference9h◆PPO-HSC: An Exploratory Reinforcement Learning Framework Based on Wide-Area Policy Coverage Optimization9h◆Is Progressive Disclosure All You Need for Long-Context Agents?9h◆It Depends on the Dataset: When a Brain-Encoding Model's Predicted Responses Beat Their Visual Backbone for Video Memorability9h◆DMFNet: Dual-Backbone Multiscale Fusion Network for Urban Scene Classification9h◆Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration9h◆Time-Frequency Consistency Learning for Robust Speech Deepfake Detection9h◆Scientific reasoning does not reliably translate into scientific forecasting in frontier AI9h◆Language Triggers Hijack Language Circuits: A Mechanistic Analysis of Backdoor Behaviors in Large Language Models9h◆Kernel Regression with Tensor Trains and Hadamard Overparameterization9h◆AI-Augmented Human Resource Management? Insights from German companies9h◆Diagnosing Correctness Probes under Self-Judgement Confounding9h◆BLAD: A Historically Contextualized, Multilingual Dataset of Bangladeshi Legal Acts (1799 to 2025)9h◆
DataBubble·

Model Detail

deepreinforce-ai logo

Ornith-1.0-397B-FP8

—
Provider: deepreinforce-aiCategory: llmPipeline: text-generationParameters: 397B
DB Score
41.6
Downloads
65K
Likes
66
Day
+0.0%
Week
+0.0%
Month
+0.0%
Overview

Ornith-1.0-397B-FP8 is a large language model with 397B parameters released by deepreinforce-ai. The model is registered under the text-generation pipeline tag on Hugging Face, distributed under the permissive mit license.

Technical

Ornith-1.0-397B-FP8 ships with 397B parameters. Total weight footprint is approximately 397.0 GB, which is the relevant figure when planning local-inference VRAM. The mit license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.

Use Cases

Ornith-1.0-397B-FP8 is best fit for general-purpose chat and instruction-following workloads. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.

Download History
Model Info
Licensemit
Related Models
deepreinforce-ai logo
Ornith-1.0-9B-GGUF
deepreinforce-ai · 2.2M downloads
deepreinforce-ai logo
Ornith-1.0-35B-GGUF
deepreinforce-ai · 1.8M downloads
google-bert logo
bert-base-uncased
google-bert · 69.6M downloads
sentence-transformers logo
paraphrase-multilingual-MiniLM-L12-v2
SBERT · 48.6M downloads
HomeModelsNews