LLM EXPLORER
 LLM Explorer: A Curated Large Language Model Directory and Analytics
Dark Theme
  LLM  List    LLM Hosting    LLM Leaderboards    Blog    Newsfeed    Advertise

Meta Llama 3 8B Instruct Onnx Fp16 by aless2212

 »  All LLMs  »  aless2212  »  Meta Llama 3 8B Instruct Onnx Fp16   URL Share it on

  11   
  Autotrain compatible   Conversational   En   Endpoints compatible   Facebook   Fp16   Instruct   Llama   Llama-3   Meta   Onnx   Pytorch   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/aless2212/Meta-Llama-3-8B-Instruct-onnx-fp16 

Meta Llama 3 8B Instruct Onnx Fp16 Benchmarks

LLME Score: 0.17995
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Meta Llama 3 8B Instruct Onnx Fp16 (aless2212/Meta-Llama-3-8B-Instruct-onnx-fp16)

Meta Llama 3 8B Instruct Onnx Fp16 Parameters and Internals

Model Type 
text generation, instruction tuned
Use Cases 
Areas:
Commercial, Research
Applications:
Instruction tuned models for assistant-like chat, Pretrained models for various natural language tasks
Primary Use Cases:
English language applications
Limitations:
Not for use in languages other than English, Requires adherence to the Use Policy and Llama 3 Community License
Considerations:
Developers may fine-tune for additional languages within license compliance.
Additional Notes 
Llama 3 is designed with openness, inclusivity, and helpfulness as core values. Testing is primarily in English, with certain potential risks and uncertainties.
Supported Languages 
English (high)
Training Details 
Data Sources:
publicly available online data
Data Volume:
15T+ tokens for pretraining, over 10M human-annotated examples for fine-tuning
Methodology:
Auto-regressive language model using an optimized transformer architecture, supervised fine-tuning and reinforcement learning with human feedback (RLHF)
Context Length:
8000
Hardware Used:
Meta's Research SuperCluster, H100-80GB GPUs
Model Architecture:
Auto-regressive language model with optimized transformer architecture
Safety Evaluation 
Methodologies:
Red teaming, Adversarial evaluations, CyberSecEval
Findings:
Equivalent or safer than models with similar coding capabilities
Risk Categories:
CBRNE threats, Cyber attacks, Child safety risks
Ethical Considerations:
Responsible AI development with safety benchmarks, iterative testing during model training, and community involvement.
Responsible Ai Considerations 
Transparency:
Uses Responsible Use Guide and tools like Meta Llama Guard 2 for transparency.
Accountability:
Meta and developers share responsibilities to avoid bias and enhance safety.
Mitigation Strategies:
Supervised fine-tuning and reinforcement learning with human feedback to align with preferences.
Input Output 
Input Format:
text only
Accepted Modalities:
text
Output Format:
text and code only
LLM NameMeta Llama 3 8B Instruct Onnx Fp16
Repository 🤗https://huggingface.co/aless2212/Meta-Llama-3-8B-Instruct-onnx-fp16 
Base Model(s)  Meta LlaMA 3 8B Instruct 16K   Moses25/Meta-LlaMA-3-8B-Instruct-16k
Model Size8b
Updated2025-02-22
Maintaineraless2212
Model Typellama
Instruction-BasedYes
Supported Languagesen
Quantization Typefp16
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.40.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typefloat16

Best Alternatives to Meta Llama 3 8B Instruct Onnx Fp16

Best Alternatives
Context / RAM
Downloads
Likes
...B Instruct Gradient 1048K 4bit1024K / 4.5 GB212
...B Instruct Gradient 1048K 8bit1024K / 8.6 GB71
...truct Gradient 1048K Bpw6 EXL21024K / 6.7 GB102
...truct Gradient 1048K Bpw5 EXL21024K / 5.8 GB70
Llama 3 8B Instruct 1048K 4bit1024K / 4.5 GB1225
Llama 3 8B Instruct 1048K 8bit1024K / 8.6 GB2817
... Gradient 1048K 8.0bpw H8 EXL21024K / 8.6 GB83
...ct Gradient 1048K Bpw2.25 EXL21024K / 3.4 GB51
Llama 3 8B Instruct 262K 2bit256K / 2.5 GB71
...B Instruct 262k V2 EXL2 6.0bpw256K / 6.7 GB111
Note: green Score (e.g. "73.2") means that the model is better than aless2212/Meta-Llama-3-8B-Instruct-onnx-fp16.

Rank the Meta Llama 3 8B Instruct Onnx Fp16 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

What open-source LLMs or SLMs are you in search of? 43470 in total.

Email us: info@extractum.io. Our Privacy Policy  | Terms and Conditions  | Suggest an improvement.
Our Social Media →  
Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
  Support LLM Explorer