cyboghostginx/Llama3.1-8B

TEXT GENERATIONPricing:Input $0.2 / Cached $0.028 / Output $0.32Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Nov 1, 2025License:llama3.1Architecture:Transformer Featherless Exclusive Cold

cyboghostginx/Llama3.1-8B is an unmodified mirror of Meta's Llama 3.1 8B base model, featuring 8 billion parameters and a substantial 131,072-token context length. This model is designed for completion tasks or as a foundational starting point for further fine-tuning, rather than direct instruction-following. It maintains the original Llama architecture and weights, making it suitable for developers seeking a pure base model for custom applications.

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cyboghostginx/Llama3.1-8B: An Unmodified Llama 3.1 Base Model

This model is a direct, unmodified mirror of Meta's Llama 3.1 8B base model, preserving its original architecture and weights. It is provided without any fine-tuning or quantization, making it a pristine foundation for various natural language processing tasks.

Key Characteristics

  • Architecture: LlamaForCausalLM with 32 layers and a 128,256-entry vocabulary.
  • Precision: Operates in bf16 (bfloat16) precision.
  • Context Length: Features an extensive context window of 131,072 tokens, allowing for processing of very long inputs.
  • Format: Available in safetensors (4 shards) and Meta's original checkpoint format.
  • Licensing: Governed by the Llama 3.1 Community License from Meta Platforms, Inc.

Intended Use Cases

  • Completion Tasks: Ideal for generating text completions based on given prompts.
  • Fine-tuning Base: Serves as an excellent starting point for developers to fine-tune for specific applications or domains.
  • Research and Development: Provides a clean, unmodified Llama 3.1 base for experimental work.

Note: This is a base model and does not include an instruction-following chat template. For chat-oriented applications, users should consider meta-llama/Llama-3.1-8B-Instruct or fine-tune this base model with an appropriate instruction dataset.