---
license: apache-2.0
---

# Opus-Samantha-Llama-3-8B



Opus-Samantha-Llama-3-8B is a SFT model made with [AutoSloth](https://colab.research.google.com/drive/1Zo0sVEb2lqdsUm9dy2PTzGySxdF9CNkc#scrollTo=MmLkhAjzYyJ4) by [macadeliccc](https://huggingface.co/macadeliccc)

## Process

- Original Model: [unsloth/llama-3-8b](https://huggingface.co/unsloth/llama-3-8b)
- Datatset: [macadeliccc/opus_samantha](https://huggingface.co/datasets/macadeliccc/opus_samantha)

- Learning Rate: 2e-05
- Steps: 2772
- Warmup Steps: 277
- Per Device Train Batch Size: 2
- Gradient Accumulation Steps 1
- Optimizer: paged_adamw_8bit
- Max Sequence Length: 4096
- Max Prompt Length: 2048
- Max Length: 2048

## 💻 Usage

```python
!pip install -qU transformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model = "macadeliccc/Opus-Samantha-Llama-3-8B"
tokenizer = AutoTokenizer.from_pretrained(model)

# Example prompt
prompt = "Your example prompt here"

# Generate a response
model = AutoModelForCausalLM.from_pretrained(model)
pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
outputs = pipeline(prompt, max_length=50, num_return_sequences=1)
print(outputs[0]["generated_text"])
```

<div align="center">
<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/made%20with%20unsloth.png" height="50" align="center" />
</div>