Transformers
Safetensors
gpt2
text-generation
Generated from Trainer
chat-completion
text-generation-inference
Instructions to use mohammadZX/at with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohammadZX/at with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("mohammadZX/at") model = AutoModelForCausalLM.from_pretrained("mohammadZX/at", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,149 Bytes
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library_name: transformers
license: apache-2.0
base_model: distilgpt2
tags:
- generated_from_trainer
pipeline_tag: chat-completion
model-index:
- name: at
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. -->
# at
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
### Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu128
- Datasets 4.1.0
- Tokenizers 0.22.0
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