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.gitattributes

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README.md

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+---
+base_model: AI-Sweden-Models/Llama-3-8B-instruct
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- llama
+- trl
+- sft
+- autoquant
+- gguf
+license: apache-2.0
+language:
+- en
+datasets:
+- kobprof/skolegpt-instruct
+---
+
+# Uploaded  model
+
+- **Compute sponsored by:** Nvidia and Arrow ECS Denmark through Danish Data Science Community
+- **Developed by:** ThatsGroes
+- **License:** apache-2.0
+- **Finetuned from model :** AI-Sweden-Models/Llama-3-8B-instruct
+
+Fine tuned for 1 epoch. 
+
+We ended up using 65.62 GB GPU memory (82.92%), of which 49.89 GB (63.04%) was used for LoRa.
+
+
+[codecarbon INFO @ 21:31:34] Energy consumed for RAM : 0.404226 kWh. RAM Power : 188.78840446472168 W
+[codecarbon INFO @ 21:31:34] Energy consumed for all GPUs : 0.625855 kWh. Total GPU Power : 82.8216447468557 W
+[codecarbon INFO @ 21:31:34] Energy consumed for all CPUs : 0.091042 kWh. Total CPU Power : 42.5 W
+[codecarbon INFO @ 21:31:34] 1.121123 kWh of electricity used since the beginning.
+
+
+This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

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