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Granite 20B Code Base FP8 by nm-testing

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  Autotrain compatible   Codegen   Endpoints compatible   Fp8   Gpt bigcode   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/nm-testing/granite-20b-code-base-FP8 

Granite 20B Code Base FP8 Benchmarks

LLME Score: 0.20443
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Granite 20B Code Base FP8 (nm-testing/granite-20b-code-base-FP8)

Granite 20B Code Base FP8 Parameters and Internals

Model Type 
Causal Language Model, Quantized
Additional Notes 
Quantized using AutoFP8 with FP8 method and static activation scheme.
Input Output 
Input Format:
Tokenized inputs as PyTorch tensors.
Accepted Modalities:
text
Output Format:
Quantized model parameters in FP8 format.
LLM NameGranite 20B Code Base FP8
Repository 🤗https://huggingface.co/nm-testing/granite-20b-code-base-FP8 
Model Size20b
Required VRAM20.4 GB
Updated2024-12-21
Maintainernm-testing
Model Typegpt_bigcode
Model Files  5.0 GB: 1-of-5   4.9 GB: 2-of-5   4.9 GB: 3-of-5   4.9 GB: 4-of-5   0.7 GB: 5-of-5
Generates CodeYes
Model ArchitectureGPTBigCodeForCausalLM
Model Max Length9223372036854775807
Transformers Version4.41.2
Tokenizer ClassGPT2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size49152
Torch Data Typebfloat16
Activation Functiongelu_pytorch_tanh

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Note: green Score (e.g. "73.2") means that the model is better than nm-testing/granite-20b-code-base-FP8.

Rank the Granite 20B Code Base FP8 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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