macadeliccc
/

Opus-Samantha-Llama-3-8B

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 ---
-library_name: transformers
-tags:
-- unsloth
-- trl
-- sft
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 ---
+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>