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 70B Instruct Marlin by mgoin

 »  All LLMs  »  mgoin  »  Meta Llama 3 70B Instruct Marlin   URL Share it on

  376   
  4-bit   4bit   Autotrain compatible   Conversational   En   Endpoints compatible   Facebook   Gptq   Instruct   Llama   Llama-3   Meta   Pytorch   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/mgoin/Meta-Llama-3-70B-Instruct-Marlin 

Meta Llama 3 70B Instruct Marlin Benchmarks

LLME Score: 0.20507
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 70B Instruct Marlin (mgoin/Meta-Llama-3-70B-Instruct-Marlin)

Meta Llama 3 70B Instruct Marlin Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Commercial, Research
Applications:
Assistant-like chat, Natural language generation tasks
Primary Use Cases:
Dialogue, General text generation
Limitations:
Use is recommended only in English, Users must comply with license agreements and acceptable use policies.
Considerations:
Developers should fine-tune models for specific languages and applications if needed.
Supported Languages 
language (English), proficiency (High)
Training Details 
Data Sources:
A new mix of publicly available online data
Data Volume:
15T+ tokens
Methodology:
Supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)
Context Length:
8000
Hardware Used:
Meta's Research SuperCluster, third-party cloud compute
Model Architecture:
Llama 3 is an auto-regressive language model with an optimized transformer architecture.
Safety Evaluation 
Methodologies:
Red teaming exercises, adversarial evaluations
Risk Categories:
CBRNE risks, cybersecurity risks, child safety risks
Ethical Considerations:
Safety evaluation included an assessment of the model's capability to handle sensitive topics responsibly.
Responsible Ai Considerations 
Fairness:
Considerations related to fairness and bias addressed.
Transparency:
Open approach and documentation on safety standards.
Accountability:
Meta is responsible for addressing misuse that arises from the model's capabilities.
Mitigation Strategies:
Safety tools such as Meta Llama Guard 2 and Code Shield are available to mitigate risks.
Input Output 
Input Format:
Text input only
Accepted Modalities:
text
Output Format:
Text and code generation
Release Notes 
Version:
1.0
Date:
April 18, 2024
Notes:
Initial release of Llama 3 family models.
LLM NameMeta Llama 3 70B Instruct Marlin
Repository 🤗https://huggingface.co/mgoin/Meta-Llama-3-70B-Instruct-Marlin 
Base Model(s)  ...a Llama 3 70B Instruct Ov Int4   fakezeta/Meta-Llama-3-70B-Instruct-ov-int4
Model Size70b
Required VRAM39.5 GB
Updated2024-12-22
Maintainermgoin
Model Typellama
Instruction-BasedYes
Model Files  39.5 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq|4bit
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.40.0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typefloat16

Best Alternatives to Meta Llama 3 70B Instruct Marlin

Best Alternatives
Context / RAM
Downloads
Likes
...B Instruct AutoRound GPTQ 4bit128K / 39.9 GB22905
...B Instruct AutoRound GPTQ 4bit128K / 39.9 GB522
...ama 3.1 70B Instruct Gptq 4bit128K / 39.9 GB3544
Meta Llama 3 70B Instruct GPTQ8K / 39.8 GB82716
...erkrautLM 70B Instruct GPTQ 8B8K / 74.4 GB4151
Meta Llama 3 70B Instruct GPTQ8K / 39.8 GB47019
...ama 3 Taiwan 70B Instruct GPTQ8K / 39.8 GB212
...g Llama 3 70B Instruct GPTQ 4B8K / 39.8 GB80
...g Llama 3 70B Instruct GPTQ 8B8K / 74.4 GB41
...a Llama 3 70B Instruct GPTQ 8B8K / 74.4 GB90
Note: green Score (e.g. "73.2") means that the model is better than mgoin/Meta-Llama-3-70B-Instruct-Marlin.

Rank the Meta Llama 3 70B Instruct Marlin 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? 40066 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 v20241217
  Support LLM Explorer