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RichardErkhov/
jiawei1018_-_openmathinstruct2-llama-3.1-8B-Instruct-gguf

Name: jiawei1018_-_openmathinstruct2-llama-3.1-8B-Instruct-gguf
Availability: InStock

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Quantization made by Richard Erkhov.

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openmathinstruct2-llama-3.1-8B-Instruct - GGUF

Model creator: https://huggingface.co/jiawei1018/
Original model: https://huggingface.co/jiawei1018/openmathinstruct2-llama-3.1-8B-Instruct/

Name	Quant method	Size
openmathinstruct2-llama-3.1-8B-Instruct.Q2_K.gguf	Q2_K	2.96GB
openmathinstruct2-llama-3.1-8B-Instruct.IQ3_XS.gguf	IQ3_XS	3.28GB
openmathinstruct2-llama-3.1-8B-Instruct.IQ3_S.gguf	IQ3_S	3.43GB
openmathinstruct2-llama-3.1-8B-Instruct.Q3_K_S.gguf	Q3_K_S	3.41GB
openmathinstruct2-llama-3.1-8B-Instruct.IQ3_M.gguf	IQ3_M	3.53GB
openmathinstruct2-llama-3.1-8B-Instruct.Q3_K.gguf	Q3_K	3.74GB
openmathinstruct2-llama-3.1-8B-Instruct.Q3_K_M.gguf	Q3_K_M	3.74GB
openmathinstruct2-llama-3.1-8B-Instruct.Q3_K_L.gguf	Q3_K_L	4.03GB
openmathinstruct2-llama-3.1-8B-Instruct.IQ4_XS.gguf	IQ4_XS	4.18GB
openmathinstruct2-llama-3.1-8B-Instruct.Q4_0.gguf	Q4_0	4.34GB
openmathinstruct2-llama-3.1-8B-Instruct.IQ4_NL.gguf	IQ4_NL	4.38GB
openmathinstruct2-llama-3.1-8B-Instruct.Q4_K_S.gguf	Q4_K_S	4.37GB
openmathinstruct2-llama-3.1-8B-Instruct.Q4_K.gguf	Q4_K	4.58GB
openmathinstruct2-llama-3.1-8B-Instruct.Q4_K_M.gguf	Q4_K_M	4.58GB
openmathinstruct2-llama-3.1-8B-Instruct.Q4_1.gguf	Q4_1	4.78GB
openmathinstruct2-llama-3.1-8B-Instruct.Q5_0.gguf	Q5_0	5.22GB
openmathinstruct2-llama-3.1-8B-Instruct.Q5_K_S.gguf	Q5_K_S	5.22GB
openmathinstruct2-llama-3.1-8B-Instruct.Q5_K.gguf	Q5_K	5.34GB
openmathinstruct2-llama-3.1-8B-Instruct.Q5_K_M.gguf	Q5_K_M	5.34GB
openmathinstruct2-llama-3.1-8B-Instruct.Q5_1.gguf	Q5_1	5.65GB
openmathinstruct2-llama-3.1-8B-Instruct.Q6_K.gguf	Q6_K	6.14GB
openmathinstruct2-llama-3.1-8B-Instruct.Q8_0.gguf	Q8_0	7.95GB

Original model description:

library_name: transformers license: llama3.1 base_model: meta-llama/Llama-3.1-8B-Instruct tags:

llama-factory
full
generated_from_trainer model-index:
name: openmathinstruct2-llama-3.1-8B-Instruct results: []

openmathinstruct2-llama-3.1-8B-Instruct

This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the openmathinstruct2_cot_20k_train dataset. It achieves the following results on the evaluation set:

Loss: 0.7514

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-06
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1.0

Training results

Framework versions

Transformers 4.45.2
Pytorch 2.3.0+cu121
Datasets 2.21.0
Tokenizers 0.20.1

RichardErkhov/jiawei1018_-_openmathinstruct2-llama-3.1-8B-Instruct-gguf

Original model description:

openmathinstruct2-llama-3.1-8B-Instruct

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
jiawei1018_-_openmathinstruct2-llama-3.1-8B-Instruct-gguf