CoolFace
Modelpublic

RichardErkhov/Spooke_-_distilgpt2-finetuned-python_code_instructions_18k_alpaca-gguf

sourceHugging Faceupdated 2y agoView on Hugging Face
0likes576downloads
Model Card

Quantization made by Richard Erkhov.

Github

Discord

Request more models

distilgpt2-finetuned-pythoncodeinstructions18kalpaca - GGUF

  • Model creator: https://huggingface.co/Spooke/
  • Original model: https://huggingface.co/Spooke/distilgpt2-finetuned-pythoncodeinstructions18kalpaca/
NameQuant methodSize
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q2_K.ggufQ2_K0.06GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.IQ3_XS.ggufIQ3_XS0.07GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.IQ3_S.ggufIQ3_S0.07GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q3_K_S.ggufQ3KS0.07GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.IQ3_M.ggufIQ3_M0.07GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q3_K.ggufQ3_K0.07GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q3_K_M.ggufQ3KM0.07GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q3_K_L.ggufQ3KL0.07GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.IQ4_XS.ggufIQ4_XS0.07GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q4_0.ggufQ4_00.08GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.IQ4_NL.ggufIQ4_NL0.08GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q4_K_S.ggufQ4KS0.08GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q4_K.ggufQ4_K0.08GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q4_K_M.ggufQ4KM0.08GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q4_1.ggufQ4_10.08GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q5_0.ggufQ5_00.09GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q5_K_S.ggufQ5KS0.09GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q5_K.ggufQ5_K0.09GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q5_K_M.ggufQ5KM0.09GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q5_1.ggufQ5_10.09GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q6_K.ggufQ6_K0.1GB
distilgpt2-finetuned-python_code_instructions_18k_alpaca.Q8_0.ggufQ8_00.12GB

Original model description: --- libraryname: transformers license: apache-2.0 basemodel: distilgpt2 tags:

  • generatedfromtrainer model-index:
  • name: distilgpt2-finetuned-pythoncodeinstructions18kalpaca results: [] ---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

distilgpt2-finetuned-pythoncodeinstructions18kalpaca

This model is a fine-tuned version of distilgpt2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4143

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: 2e-05
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 7

Training results

Training LossEpochStepValidation Loss
1.71181.038621.5780
1.58382.077241.4955
1.49143.0115861.4615
1.45324.0154481.4364
1.42925.0193101.4241
1.41366.0231721.4171
1.37787.0270341.4143

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1