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akumaburn/Alpaca-Llama-3-8B
Alpaca-Llama-3-8B is a text generation model from akumaburn. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
- Fine Tuned using dataset: https://huggingface.co/datasets/yahma/alpaca-cleaned - Epoch Count: 1 - Step Count: 6,470/6,470 - Batch Size: 2 - Gradient Accumulation Steps: 4 - Context Size: 8192 - Num examples: 51,760…
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From the Hugging Face model README
Fine Tuned using dataset: https://huggingface.co/datasets/yahma/alpaca-cleaned
Epoch Count: 1
Step Count: 6,470/6,470
Batch Size: 2
Gradient Accumulation Steps: 4
Context Size: 8192
Num examples: 51,760
Trainable Parameters: 41,943,040
Learning Rate: 0.00001
Training Loss: 0.960000
Fined Tuned using: Google Colab Pro (Nvidia T4 runtime)
Developed by: akumaburn
License: apache-2.0
Finetuned from model : unsloth/llama-3-8b-bnb-4bit
Prompt Format: Alpaca (https://libertai.io/apis/text-generation/prompting.html)
Chai ELO: 1146.84 (https://console.chaiverse.com/models/akumaburn-alpaca-llama-3-8b_v1)
Some GGUF quantizations can be found in https://huggingface.co/akumaburn/Alpaca-Llama-3-8B-GGUF
mistral-7b-openorca.Q8_0.gguf:
llama-3-8b-bnb-4bit.Q8_0.gguf:
Open_Orca_Llama-3-8B-unsloth.Q8_0.gguf:
Alpaca-Llama-3-8B-GGUF-unsloth.Q8_0.gguf:
Meta-Llama-3-8B.Q8_0.gguf:
Llama.cpp Options For Testing: --samplers "tfs;typical;temp" --draft 32 --ctx-size 8192 --temp 0.82 --tfs 0.8 --typical 1.1 --repeat-last-n 512 --batch-size 8192 --repeat-penalty 1.0 --n-gpu-layers 100 --threads 12
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.