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Granite 20B Code Base by ibm-granite

 »  All LLMs  »  ibm-granite  »  Granite 20B Code Base   URL Share it on

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  Arxiv:2405.04324   Autotrain compatible   Code   Codegen   Dataset:bigcode/starcoderdata Dataset:codeparrot/github-code...   Dataset:math-ai/stackmathqa Dataset:open-web-math/open-web...   Endpoints compatible   Gpt bigcode   Granite   Model-index   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/ibm-granite/granite-20b-code-base 

Granite 20B Code Base Benchmarks

LLME Score: 0.17107
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 (ibm-granite/granite-20b-code-base)
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Granite 20B Code Base Parameters and Internals

Model Type 
code generation, decoder-only, text-generation
Use Cases 
Areas:
enterprise use, software engineering productivity
Applications:
code generation, code explanation, code fixing, generating unit tests, generating documentation, addressing technical debt issues, vulnerability detection, code translation
Limitations:
Risks of problematic outputs, No safety alignment, Increased susceptibility to hallucination
Considerations:
Caution against complete reliance for crucial decisions
Supported Languages 
116 programming languages (comprehensive)
Training Details 
Data Sources:
Publicly available datasets from GitHub Code Clean, Starcoder data
Data Volume:
3 trillion tokens (Phase 1), 500 billion tokens (Phase 2)
Methodology:
Two-phase training strategy (comprehensive understanding, improved reasoning)
Hardware Used:
IBM's Vela and Blue Vela supercomputing clusters, NVIDIA A100 and H100 GPUs
Model Architecture:
Decoder-only code model
Safety Evaluation 
Risk Categories:
malicious utilization, unsafe code generation
Ethical Considerations:
The generated code is not guaranteed to work as intended, risks of malicious use.
Responsible Ai Considerations 
Mitigation Strategies:
HAP, PII, Malware Filtering
Release Notes 
Date:
May 6th, 2024
Notes:
Model released with decoder-only architecture suited for code generative tasks.
LLM NameGranite 20B Code Base
Repository 🤗https://huggingface.co/ibm-granite/granite-20b-code-base 
Model Size20b
Required VRAM40 GB
Updated2024-09-01
Maintaineribm-granite
Model Typegpt_bigcode
Model Files  5.0 GB: 1-of-9   4.9 GB: 2-of-9   4.9 GB: 3-of-9   4.9 GB: 4-of-9   4.9 GB: 5-of-9   4.9 GB: 6-of-9   4.9 GB: 7-of-9   4.9 GB: 8-of-9   0.7 GB: 9-of-9
Generates CodeYes
Model ArchitectureGPTBigCodeForCausalLM
Licenseapache-2.0
Model Max Length9223372036854775807
Transformers Version4.38.1
Tokenizer ClassGPT2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size49152
Torch Data Typebfloat16
Activation Functiongelu_pytorch_tanh

Quantized Models of the Granite 20B Code Base

Model
Likes
Downloads
VRAM
Granite 20B Code Base GGUF04012 GB

Best Alternatives to Granite 20B Code Base

Best Alternatives
Context / RAM
Downloads
Likes
Granite 20B Code Instruct0K / 40 GB1020930
Granite 20B Functioncalling0K / 40 GB116834
Granite 20B Code Instruct 8K0K / 40 GB188642
Granite 20B Code Base 8K0K / 40 GB164414
Granite 20B Code Base R1.10K / 40 GB702
Granite 20B Code Instruct R1.10K / 40 GB551
Granite 20B Code Base FP80K / 20.4 GB70
Granite 20B Code Base GGUF0K / 12.8 GB400
Note: green Score (e.g. "73.2") means that the model is better than ibm-granite/granite-20b-code-base.

Rank the Granite 20B Code Base 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  

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Release v20241124
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