---
library_name: transformers
license: mit
language:
- en
base_model: Salesforce/codegen-350M-multi
---

# Model Card for Model ID

Model finetuned to autocomplete for YAML files 8 bit quantized version of https://huggingface.co/alexvumnov/yaml_completion



## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** https://huggingface.co/alexvumnov
- **Model type:** Autoregressive decoder only transformer (GPT2-based)
- **Language(s) (NLP):** English, but mostly YAML
- **License:**  MIT
- **Finetuned from model [optional]:** https://huggingface.co/Salesforce/codegen-350M-multi/tree/main


## Uses

Model expects a specific prompt format, so please use it for best performance

```python
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline

model = AutoModelForCausalLM.from_pretrained("alexvumnov/yaml_completion")
tokenizer = AutoTokenizer.from_pretrained("alexvumnov/yaml_completion", padding='left')

prompt_format = """
# Here's a yaml file to offer a completion for
# Lines after the current one
{text_after}
# Lines before the current one
{text_before}
# Completion:
"""

input_prefix = """
name: my_awesome_env
dependencies:

"""

input_suffix = ""

generator = pipeline('text-generation', model=model, tokenizer=tokenizer, device='cuda')

generator(prompt_format.format(text_after=input_suffix, text_before=input_prefix), max_new_tokens=64)

# [{'generated_text': "\n# Here's a yaml file to offer a completion for\n# Lines after the current one\n\n# Lines before the current one\n\nname: my_awesome_env\ndependencies:\n\n\n# Completion:\n- deploy"}]
```