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# git-base-instagram-cap

This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an 
[mrSoul7766/instagram_post_captions](https://huggingface.co/datasets/mrSoul7766/instagram_post_captions).

It achieves the following results on the evaluation set:
- Loss: 0.0093


### Usage

you can leverage the capabilities provided by the Hugging Face Transformers library. Here's a basic example using Python:

```python
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-to-text", model="mrSoul7766/git-base-instagram-cap")

# Generate caption
caption = pipe("/content/download (12).png",max_new_tokens =100)

# Print the generated answer
print(caption[0]['generated_text'])
```
```
i love my blonde character in kim kardashian hollywood! i'm playing now who's playing with me?
```

### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
{"language": ["en"], "license": "mit", "tags": ["generated_from_trainer", "image-to-text", "image-captioning"], "base_model": "microsoft/git-base", "pipeline_tag": "image-to-text", "model-index": [{"name": "git-base-instagram-cap", "results": []}]}
transformers tensorboard safetensors git text-generation generated_from_trainer image-to-text image-captioning en base_model:microsoft/git-base license:mit autotrain_compatible endpoints_compatible region:us