daman1209arora/Reliability-1.7B-final-brier-ckpt-600

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:2BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Sep 17, 2026Architecture:Transformer Featherless Exclusive Cold

The daman1209arora/Reliability-1.7B-final-brier-ckpt-600 is a 1.7 billion parameter Qwen3ForCausalLM model checkpoint, specifically from the `Reliability-1.7B-final/brier_1e-6_rloo` training run at global step 600. This model provides exported weights in BF16 safetensors format, along with its configuration and tokenizer files. It is designed as a causal language model, suitable for tasks requiring text generation and understanding based on its training. Its 32768 token context length supports processing longer sequences.

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Model Overview

The daman1209arora/Reliability-1.7B-final-brier-ckpt-600 is a 1.7 billion parameter causal language model based on the Qwen3ForCausalLM architecture. This specific release represents a checkpoint taken at global training step 600 from the Reliability-1.7B-final/brier_1e-6_rloo training run.

Key Characteristics

  • Architecture: Qwen3ForCausalLM, a transformer-based causal language model.
  • Parameters: 1.7 billion, offering a balance between performance and computational efficiency.
  • Context Length: 32768 tokens, enabling the model to process and generate longer text sequences.
  • Format: Model weights are provided in BF16 safetensors format, suitable for efficient loading and inference.
  • Components: The repository includes the model weights, configuration files, and tokenizer files, providing a complete package for deployment.

Potential Use Cases

This model is suitable for a variety of natural language processing tasks, including:

  • Text generation
  • Code completion
  • Question answering
  • Summarization
  • General conversational AI applications