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| | base_model: dineth554/legion-coder-8m |
| | library_name: transformers |
| | license: mit |
| | pipeline_tag: text-generation |
| | language: |
| | - en |
| | - code |
| | tags: |
| | - transformers |
| | - pytorch |
| | - safetensors |
| | - text-generation |
| | - code-generation |
| | - python |
| | - javascript |
| | - coding |
| | - programming |
| | - sagemaker |
| | - amazon-sagemaker |
| | - cpu |
| | - compact |
| | - efficient |
| | - nvdya-kit |
| | - death-legion |
| |
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| | datasets: |
| | - the-stack-v2 |
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| | metrics: |
| | - perplexity |
| | - accuracy |
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| | model-index: |
| | - name: Legion Coder 8M |
| | results: [] |
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| | inference: |
| | parameters: |
| | temperature: 0.8 |
| | top_p: 0.95 |
| | top_k: 50 |
| | max_new_tokens: 200 |
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|
| | sagemaker: |
| | sdk_version: "2.200.0" |
| | instance_type: "ml.m5.large" |
| | instance_count: 1 |
| | container_image: "huggingface-pytorch-inference:2.0.0-transformers4.28.1-cpu-py310-ubuntu20.04-v1.0" |
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| | |
| | model_details: |
| | name: Legion Coder 8M |
| | version: 1.0.0 |
| | description: A compact yet powerful 44M parameter transformer model optimized for coding tasks |
| | developer: DEATH LEGION |
| | powered_by: nvdya-kit |
| | architecture: GPT-style Transformer |
| | parameters: 44,341,632 |
| | model_size: 170MB |
| | hidden_size: 576 |
| | num_layers: 13 |
| | num_heads: 16 |
| | context_length: 1024 |
| | vocabulary_size: 16000 |
| | format: Safetensors |
| | precision: float32 |
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| | |
| | training_details: |
| | optimizer: AdamW |
| | learning_rate: 5e-4 |
| | lr_schedule: cosine_decay |
| | batch_size: 4 |
| | gradient_accumulation: true |
| | training_steps: 10000 |
| | precision: float32 |
| |
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| | |
| | intended_use: |
| | primary_use_cases: |
| | - Code completion and generation |
| | - Function generation from descriptions |
| | - Debugging assistance |
| | - Code explanation and documentation |
| | - Programming concept explanations |
| | - Code scaffolding and prototyping |
| | target_users: |
| | - Software developers |
| | - Students learning to code |
| | - Data scientists |
| | - DevOps engineers |
| | - Technical writers |
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| | |
| | limitations: |
| | - Limited to 1,024 token context window |
| | - Trained primarily on Python code |
| | - May generate code that requires review before production use |
| | - Not suitable for non-coding tasks |
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| | |
| | ethical_considerations: |
| | - Generated code should be reviewed before deployment |
| | - May reproduce patterns from training data |
| | - Not a replacement for human code review |
| | - Users are responsible for compliance with licenses of generated code |
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|
| | |
| | citation: | |
| | @misc{legioncoder2026, |
| | title={Legion Coder 8M: A Compact Transformer for Code Generation}, |
| | author={DEATH LEGION}, |
| | year={2026}, |
| | howpublished={\url{https://huggingface.co/dineth554/legion-coder-8m}} |
| | } |
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| | |
| | contact: |
| | developer: DEATH LEGION |
| | powered_by: nvdya-kit |
| | repository: https://huggingface.co/dineth554/legion-coder-8m |
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| | |
| | branding: |
| | tagline: MADE WITH BY DEATH LEGION |
| | powered_by: nvdya-kit |
| | copyright: 2026 DEATH LEGION. All rights reserved. |
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