π§ Model
llama-3-Korean-Bllossom-8B
by MLP-KTLim
llama-3-Korean-Bllossom-8B is an open-source AI model by MLP-KTLim
π Updated 12/31/2025
Technical Specifications
Parameters8.03
ArchitectureLlamaForCausalLM
View Config (3 entries)
{
"architectures": [
"LlamaForCausalLM"
],
"model_type": "llama",
"tokenizer_config": {
"bos_token": "<|begin_of_text|>",
"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
"eos_token": "<|eot_id|>",
"pad_token": "<|end_of_text|>"
}
}
πΎ
Est. VRAM Required
~7 GB
Estimation Formula
VRAM = params Γ 0.6 + 2 GB
Based on FP16 precision.
β οΈ Does not account for KV cache or parallel overhead.
π Estimate only. Actual requirements may vary.
π Daily sync (11:00 Beijing)
Based on open-source metadata snapshot. Last synced: Dec 31, 2025
π§ Architecture Explorer
Neural network architecture
1 Input Layer
2 Hidden Layers
3 Attention
4 Output Layer
Parameters 8.03B
Technical Specifications
Parameters8.03
ArchitectureLlamaForCausalLM
0View Config (3 entries)
{
"architectures": [
"LlamaForCausalLM"
],
"model_type": "llama",
"tokenizer_config": {
"bos_token": "<|begin_of_text|>",
"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
"eos_token": "<|eot_id|>",
"pad_token": "<|end_of_text|>"
}
}
π Limitations & Considerations
- β’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
- β’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
- β’ FNI scores are relative rankings and may change as new models are added.
- β License Unknown: Verify licensing terms before commercial use.
- β’ Source: Huggingface
π Related Resources
π Related Papers
No related papers linked yet. Check the model's official documentation for research papers.
π Training Datasets
Training data information not available. Refer to the original model card for details.
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