VinitaNair_-_output-gguf – AI Model by RichardErkhov | AlphaNeural AI

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VinitaNair_-_output-gguf

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Quantization made by Richard Erkhov.

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output - GGUF

Model creator: https://huggingface.co/VinitaNair/
Original model: https://huggingface.co/VinitaNair/output/

Name	Quant method	Size
output.Q2_K.gguf	Q2_K	0.54GB
output.IQ3_XS.gguf	IQ3_XS	0.58GB
output.IQ3_S.gguf	IQ3_S	0.6GB
output.Q3_K_S.gguf	Q3_K_S	0.6GB
output.IQ3_M.gguf	IQ3_M	0.61GB
output.Q3_K.gguf	Q3_K	0.64GB
output.Q3_K_M.gguf	Q3_K_M	0.64GB
output.Q3_K_L.gguf	Q3_K_L	0.68GB
output.IQ4_XS.gguf	IQ4_XS	0.7GB
output.Q4_0.gguf	Q4_0	0.72GB
output.IQ4_NL.gguf	IQ4_NL	0.72GB
output.Q4_K_S.gguf	Q4_K_S	0.72GB
output.Q4_K.gguf	Q4_K	0.75GB
output.Q4_K_M.gguf	Q4_K_M	0.75GB
output.Q4_1.gguf	Q4_1	0.77GB
output.Q5_0.gguf	Q5_0	0.83GB
output.Q5_K_S.gguf	Q5_K_S	0.83GB
output.Q5_K.gguf	Q5_K	0.85GB
output.Q5_K_M.gguf	Q5_K_M	0.85GB
output.Q5_1.gguf	Q5_1	0.89GB
output.Q6_K.gguf	Q6_K	0.95GB
output.Q8_0.gguf	Q8_0	1.23GB

Original model description:

library_name: transformers license: llama3.2 base_model: meta-llama/Llama-3.2-1B tags:

generated_from_trainer model-index:
name: output results: []

output

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.5076

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: 1e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Use adafactor and the args are: No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1
training_steps: 200

Training results

Name	Quant method	Size
output.Q2_K.gguf	Q2_K	0.54GB
output.IQ3_XS.gguf	IQ3_XS	0.58GB
output.IQ3_S.gguf	IQ3_S	0.6GB
output.Q3_K_S.gguf	Q3_K_S	0.6GB
output.IQ3_M.gguf	IQ3_M	0.61GB
output.Q3_K.gguf	Q3_K	0.64GB
output.Q3_K_M.gguf	Q3_K_M	0.64GB
output.Q3_K_L.gguf	Q3_K_L	0.68GB
output.IQ4_XS.gguf	IQ4_XS	0.7GB
output.Q4_0.gguf	Q4_0	0.72GB
output.IQ4_NL.gguf	IQ4_NL	0.72GB
output.Q4_K_S.gguf	Q4_K_S	0.72GB
output.Q4_K.gguf	Q4_K	0.75GB
output.Q4_K_M.gguf	Q4_K_M	0.75GB
output.Q4_1.gguf	Q4_1	0.77GB
output.Q5_0.gguf	Q5_0	0.83GB
output.Q5_K_S.gguf	Q5_K_S	0.83GB
output.Q5_K.gguf	Q5_K	0.85GB
output.Q5_K_M.gguf	Q5_K_M	0.85GB
output.Q5_1.gguf	Q5_1	0.89GB
output.Q6_K.gguf	Q6_K	0.95GB
output.Q8_0.gguf	Q8_0	1.23GB

Framework versions

Transformers 4.46.3
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.20.3