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Incoder 1B by facebook

 »  All LLMs  »  facebook  »  Incoder 1B   URL Share it on

  512   
  Arxiv:2204.05999   Autotrain compatible   Code   Endpoints compatible   Javascript   Python   Pytorch   Region:us   Xglm
Model Card on HF 🤗: https://huggingface.co/facebook/incoder-1B 

Incoder 1B Benchmarks

LLME Score: 0.01353
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Incoder 1B (facebook/incoder-1B)
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Incoder 1B Parameters and Internals

Model Type 
decoder-only, Transformer
Use Cases 
Areas:
code generation, code infilling
Additional Notes 
A larger, 6B parameter model is also available at facebook/incoder-6B.
Supported Languages 
Python (primary), JavaScript (primary), Others (28 languages)
Training Details 
Data Sources:
public open-source repositories from GitHub, GitLab, StackOverflow
Methodology:
trained on public open-source repositories with a permissive, non-copyleft, license (Apache 2.0, MIT, BSD-2 or BSD-3)
Model Architecture:
decoder-only Transformer
Input Output 
Performance Tips:
When calling `tokenizer.decode`, it's important to pass `clean_up_tokenization_spaces=False` to avoid removing spaces after punctuation.
LLM NameIncoder 1B
Repository 🤗https://huggingface.co/facebook/incoder-1B 
Model Size1b
Required VRAM2.6 GB
Updated2025-09-23
Maintainerfacebook
Model Typexglm
Model Files  2.6 GB
Model ArchitectureXGLMForCausalLM
Licensecc-by-nc-4.0
Context Length2048
Model Max Length2048
Transformers Version4.18.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size50518
Torch Data Typefloat16
Activation Functiongelu

Best Alternatives to Incoder 1B

Best Alternatives
Context / RAM
Downloads
Likes
Incoder 1B Finetuned Jest0.5K / 2.1 GB261
Incoder 1B Finetuned Jest0.5K / 2.1 GB71
Note: green Score (e.g. "73.2") means that the model is better than facebook/incoder-1B.

Rank the Incoder 1B 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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