Neo 7B Sft V0.1 by m-a-p

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  Autotrain compatible   Conversational   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF ๐Ÿค—: https://huggingface.co/m-a-p/neo_7b_sft_v0.1 

Neo 7b Sft V0.1 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Neo 7B Sft V0.1 (m-a-p/neo_7b_sft_v0.1)

Neo 7B Sft V0.1 Parameters and Internals

Model Type 
Large Language Model, Bilingual Model
Additional Notes 
NEO is a completely open source large language model with available code, model weights, datasets, and training details.
Supported Languages 
bilingual (unknown)
Training Details 
Data Sources:
source A, source B
Data Volume:
3.7T tokens for intermediate phase, 720B tokens for decay phase
Methodology:
standard pre-training and fine-tuning techniques
Training Time:
unknown
Hardware Used:
unknown
Model Architecture:
unknown
Input Output 
Input Format:
formatted using chat template
Accepted Modalities:
text
Output Format:
text
LLM NameNeo 7b Sft V0.1
Repository ๐Ÿค—https://huggingface.co/m-a-p/neo_7b_sft_v0.1 
Model Size7b
Required VRAM15.5 GB
Updated2025-02-22
Maintainerm-a-p
Model Typellama
Model Files  4.8 GB: 1-of-4   4.9 GB: 2-of-4   5.0 GB: 3-of-4   0.8 GB: 4-of-4
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.40.0
Tokenizer ClassNEOTokenizer
Padding Token<unk>
Vocabulary Size64256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than m-a-p/neo_7b_sft_v0.1.

Rank the Neo 7B Sft V0.1 Capabilities

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Instruction Following and Task Automation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227