Vivian12300_-_en_sw_wiki_en-gguf – AI Model by RichardErkhov | AlphaNeural AI

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Vivian12300_-_en_sw_wiki_en-gguf

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en_sw_wiki_en - GGUF

Model creator: https://huggingface.co/Vivian12300/
Original model: https://huggingface.co/Vivian12300/en_sw_wiki_en/

Name	Quant method	Size
en_sw_wiki_en.Q2_K.gguf	Q2_K	2.96GB
en_sw_wiki_en.IQ3_XS.gguf	IQ3_XS	3.28GB
en_sw_wiki_en.IQ3_S.gguf	IQ3_S	3.43GB
en_sw_wiki_en.Q3_K_S.gguf	Q3_K_S	3.41GB
en_sw_wiki_en.IQ3_M.gguf	IQ3_M	3.52GB
en_sw_wiki_en.Q3_K.gguf	Q3_K	3.74GB
en_sw_wiki_en.Q3_K_M.gguf	Q3_K_M	3.74GB
en_sw_wiki_en.Q3_K_L.gguf	Q3_K_L	4.03GB
en_sw_wiki_en.IQ4_XS.gguf	IQ4_XS	4.18GB
en_sw_wiki_en.Q4_0.gguf	Q4_0	4.34GB
en_sw_wiki_en.IQ4_NL.gguf	IQ4_NL	4.38GB
en_sw_wiki_en.Q4_K_S.gguf	Q4_K_S	4.37GB
en_sw_wiki_en.Q4_K.gguf	Q4_K	4.58GB
en_sw_wiki_en.Q4_K_M.gguf	Q4_K_M	4.58GB
en_sw_wiki_en.Q4_1.gguf	Q4_1	4.78GB
en_sw_wiki_en.Q5_0.gguf	Q5_0	5.21GB
en_sw_wiki_en.Q5_K_S.gguf	Q5_K_S	5.21GB
en_sw_wiki_en.Q5_K.gguf	Q5_K	5.34GB
en_sw_wiki_en.Q5_K_M.gguf	Q5_K_M	5.34GB
en_sw_wiki_en.Q5_1.gguf	Q5_1	5.65GB
en_sw_wiki_en.Q6_K.gguf	Q6_K	6.14GB
en_sw_wiki_en.Q8_0.gguf	Q8_0	7.95GB

Original model description:

library_name: transformers license: llama3.1 base_model: Vivian12300/sparse_ft_en_sw tags:

trl
sft
generated_from_trainer datasets:
generator model-index:
name: sparse_ft_en_sw_context results: []

sparse_ft_en_sw_context

This model is a fine-tuned version of Vivian12300/sparse_ft_en_sw on the generator dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 1
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Use adafactor and the args are: No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 30

Training results

Framework versions

Transformers 4.46.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.20.3