Hermes-A1-20B

Hermes-A1-20B is a 20-billion parameter multilingual large language model (LLM) built on top of GPT-OSS-20B. Hermes-A1-20B extends the capabilities of the original model with enhanced multilingual understanding, generation, and reasoning, making it suitable for research and production applications across diverse languages.

The model is designed to perform a wide range of tasks, including natural language understanding, code completion, translation, summarisation, and complex reasoning, all with multilingual support.

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Model Highlights

Feature	Description
Base Model	GPT-OSS-20B
Parameters	20B
Architecture	Transformer-based causal language model
Training Objective	Autoregressive causal language modeling
Multilingual Support	Enhanced embeddings for multiple languages (see metadata for full list)
Applications	Chatbots, text completion, translation, code generation, reasoning tasks

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Technical Overview

Hermes-A1-20B builds on GPT-OSS-20B while introducing several key enhancements:

1. Multilingual Tokenization and Embeddings

   • Improved tokenization and embedding layers to handle multiple languages.
   • Optimized for high-frequency languages as well as low-resource languages (coverage listed in metadata).

2. Architecture

   • 20B parameters, 64 attention layers (example, adjust per your actual config), causal self-attention.
   • Supports long-context sequences with memory-efficient attention.

3. Training Details

   • Initialized from GPT-OSS-20B weights.
   • Fine-tuned on a curated multilingual corpus.
   • Mixed-precision training with distributed GPU clusters for efficiency.

4. Inference Optimization

   • Supports batch and streaming generation.
   • Can be deployed on GPU and CPU for research or production applications.

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Supported Languages

Hermes-A1-20B supports multiple languages for both comprehension and generation. For the full list of languages, please check the model metadata on Hugging Face.

Example language families:

• English, Spanish, French, German, Portuguese
• Chinese (Simplified & Traditional), Japanese, Korean
• Hindi, Arabic, Russian, Turkish
• Other regional languages with partial coverage

Performance may vary depending on language resources and training data coverage.

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Use Cases

1. Conversational AI and Multilingual Chatbots

   • Engage in context-aware conversations across supported languages.

2. Text Generation and Completion

   • Story writing, creative content generation, and automated summarization.

3. Code Generation & Comprehension

   • Supports programming languages and natural language code prompts.

4. Multilingual Translation & Summarization

   • Translate text between supported languages.
   • Summarize documents in multiple languages.

5. Reasoning and Knowledge Tasks

   • Handles multi-step reasoning queries, QA systems, and educational tasks.

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Example Usage

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Spestly/Hermes-A1-20B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

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Limitations

• Performance varies by language and domain; low-resource languages may be less accurate.
• May generate plausible but incorrect or biased outputs. Human oversight recommended.
• Not recommended for safety-critical applications without evaluation.

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Citation

@misc{hermes-a1-20b,
  title={Hermes-A1-20B: A Multilingual Large Language Model},
  author={Aayan mishra},
  year={2025},
  url={https://huggingface.co/Spestly/Hermes-A1-20B/}
}