---
library_name: peft
base_model: meta-llama/Llama-2-7b-hf
license: llama2
datasets:
- freQuensy23/toxic-answers
language:
- en
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->



## Model Details

### Model Description

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



- **Developed by: t.me/freQuensy23
- **Model type: LLM (Llama2)
- **Language(s) (NLP): EN
- **License:** Llama-2-license
- **Finetuned from model [optional]: meta-llama/Llama-2-7b
### Model Sources [optional]

## How to Get Started with the Model

```python
import peft
import transformers
model = peft.AutoPeftModelForCausalLM.from_pretrained('freQuensy23/toxic-llama2')
tokenizer = transformers.AutoTokenizer.from_pretrained('transformers')

print(tokenizer.batch_decode(input_ids=tokenizer('User: What is 1 + 8?\nBot:', return_tensors='pt').input_ids))
```

[More Information Needed]

## Training Details

### Training Data
https://huggingface.co/freQuensy23/toxic-llama2

[More Information Needed]
 
### Results


## Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** A-100
- **Hours used:** 1
- **Cloud Provider:** Yandex-cloud
- **Compute Region:** Moscow
- **Carbon Emitted:** 11g

## Model Card Contact

t.me/freQuensy23
github.com/freQuensy23-coder
mametev.av@phystech.edu


### Framework versions

- PEFT 0.7.1