BueormLLC_-_GPT2Coder-gguf

RichardErkhov/BueormLLC_-_GPT2Coder-gguf

BueormLLC_-_GPT2Coder-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.

Downloads · 30 days

2% of all-time downloads

All-time downloads

1.1K

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Repo size

1.8 GB

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Public

Hugging Face

Repo makeup

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.gguf2.2 GB · 100%

At a glance

Access: Public
Created: Nov 3, 2024
Updated: Nov 3, 2024
SHA: 52cf3804

Model card

From the Hugging Face model README

Quantization made by Richard Erkhov.

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GPT2Coder - GGUF

Model creator: https://huggingface.co/BueormLLC/
Original model: https://huggingface.co/BueormLLC/GPT2Coder/

Name	Quant method	Size
GPT2Coder.Q2_K.gguf	Q2_K	0.08GB
GPT2Coder.Q3_K_S.gguf	Q3_K_S	0.08GB
GPT2Coder.Q3_K.gguf	Q3_K	0.09GB
GPT2Coder.Q3_K_M.gguf	Q3_K_M	0.09GB
GPT2Coder.Q3_K_L.gguf	Q3_K_L	0.1GB
GPT2Coder.IQ4_XS.gguf	IQ4_XS	0.1GB
GPT2Coder.Q4_0.gguf	Q4_0	0.1GB
GPT2Coder.IQ4_NL.gguf	IQ4_NL	0.1GB
GPT2Coder.Q4_K_S.gguf	Q4_K_S	0.1GB
GPT2Coder.Q4_K.gguf	Q4_K	0.11GB
GPT2Coder.Q4_K_M.gguf	Q4_K_M	0.11GB
GPT2Coder.Q4_1.gguf	Q4_1	0.11GB
GPT2Coder.Q5_0.gguf	Q5_0	0.11GB
GPT2Coder.Q5_K_S.gguf	Q5_K_S	0.11GB
GPT2Coder.Q5_K.gguf	Q5_K	0.12GB
GPT2Coder.Q5_K_M.gguf	Q5_K_M	0.12GB
GPT2Coder.Q5_1.gguf	Q5_1	0.12GB
GPT2Coder.Q6_K.gguf	Q6_K	0.13GB
GPT2Coder.Q8_0.gguf	Q8_0	0.17GB

Original model description:

license: mit datasets:

agicorp/python_code_instructions_18k_alpaca language:
en base_model:
openai-community/gpt2 pipeline_tag: text-generation library_name: transformers tags:
code

Model Card

GPT2Coder is a language model that uses openAI's GPT2 model architecture, the model was pre-trained on multiple code data focused on python and languages such as Spanish and English.

It is a pre-trained model in a medium amount of code, so it is not recommended to use it like this, but it is functional and serves uses such as fine tuning and other tasks.

Model Details

Developed by: BueormAI
Shared by: BueormLLC
Model type: Transformer
Language(s) (NLP): English (en), Spanish (es)
License: MiT
Finetuned from model: GPT2 Architecture

Bias, Risks, and Limitations

The model can generate unexpected code and output, in addition to offensive texts and non-functional code.

Recommendations

We recommend using the model with caution and handling its outputs with discretion as they may turn out to be non-functional outputs and harmful and dangerous code.

Training Details

Training Hyperparameters

Training regime: fp16 mixed precision
Max_lenght: 1024 tokens
pretrain epochs: 1 epochs
finetuning epochs: 2 epochs

Environmental Impact

Hardware Type: GPU P100
Hours used: 18 hours
Cloud Provider: Kaggle

By Bueorm

Thanks to all the people who download and support our projects and manage a vision towards the future with AI, we hope you will support us to continue advancing and launching more followed models.

Created: Nov 3, 2024
Updated: Nov 3, 2024