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RichardErkhov/ReBatch_-_Llama-3-8B-dutch-gguf
ReBatch_-_Llama-3-8B-dutch-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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From the Hugging Face model README
Quantization made by Richard Erkhov.
Llama-3-8B-dutch - GGUF
| Name | Quant method | Size |
|---|---|---|
| Llama-3-8B-dutch.Q2_K.gguf | Q2_K | 2.96GB |
| Llama-3-8B-dutch.IQ3_XS.gguf | IQ3_XS | 3.28GB |
| Llama-3-8B-dutch.IQ3_S.gguf | IQ3_S | 3.43GB |
| Llama-3-8B-dutch.Q3_K_S.gguf | Q3_K_S | 3.41GB |
| Llama-3-8B-dutch.IQ3_M.gguf | IQ3_M | 3.52GB |
| Llama-3-8B-dutch.Q3_K.gguf | Q3_K | 3.74GB |
| Llama-3-8B-dutch.Q3_K_M.gguf | Q3_K_M | 3.74GB |
| Llama-3-8B-dutch.Q3_K_L.gguf | Q3_K_L | 4.03GB |
| Llama-3-8B-dutch.IQ4_XS.gguf | IQ4_XS | 4.18GB |
| Llama-3-8B-dutch.Q4_0.gguf | Q4_0 | 4.34GB |
| Llama-3-8B-dutch.IQ4_NL.gguf | IQ4_NL | 4.38GB |
| Llama-3-8B-dutch.Q4_K_S.gguf | Q4_K_S | 4.37GB |
| Llama-3-8B-dutch.Q4_K.gguf | Q4_K | 4.58GB |
| Llama-3-8B-dutch.Q4_K_M.gguf | Q4_K_M | 4.58GB |
| Llama-3-8B-dutch.Q4_1.gguf | Q4_1 | 4.78GB |
| Llama-3-8B-dutch.Q5_0.gguf | Q5_0 | 5.21GB |
| Llama-3-8B-dutch.Q5_K_S.gguf | Q5_K_S | 5.21GB |
| Llama-3-8B-dutch.Q5_K.gguf | Q5_K | 5.34GB |
| Llama-3-8B-dutch.Q5_K_M.gguf | Q5_K_M | 5.34GB |
| Llama-3-8B-dutch.Q5_1.gguf | Q5_1 | 5.65GB |
| Llama-3-8B-dutch.Q6_K.gguf | Q6_K | 6.14GB |
| Llama-3-8B-dutch.Q8_0.gguf | Q8_0 | 7.95GB |
license: llama3 base_model: meta-llama/Meta-Llama-3-8B tags:
This model is a QLORA and ORPO fine-tuned version of meta-llama/Meta-Llama-3-8B on the synthetic feedback dataset BramVanroy/ultra_feedback_dutch
This model is a Dutch chat model, originally developed from Llama 3 8B and further refined through a feedback dataset with ORPO and trained on BramVanroy/ultra_feedback_dutch
Although the model has been aligned with gpt-4-turbo output, which has strong content filters, the model could still generate wrong, misleading, and potentially even offensive content. Use at your own risk.
The model was trained in bfloat16 with QLORA with flash attention 2 on one GPU - H100 80GB SXM5 for around 24 hours on RunPod.
The model was evaluated using scandeval
The model showed mixed results across different benchmarks; it exhibited slight improvements on some while experiencing a decrease in scores on others. This occurred despite being trained on only 200,000 samples for a single epoch. We are curious to see whether its performance could be enhanced by training with more data or additional epochs.
| Model | conll_nl | dutch_social | scala_nl | squad_nl | wiki_lingua_nl | mmlu_nl | hellaswag_nl |
|---|---|---|---|---|---|---|---|
| meta-llama/Meta-Llama-3-8B-Instruct | 68.72 | 14.67 | 32.91 | 45.36 | 67.62 | 36.18 | 33.91 |
| ReBatch/Llama-3-8B-dutch | 58.85 | 11.14 | 15.58 | 59.96 | 64.51 | 36.27 | 28.34 |
| meta-llama/Meta-Llama-3-8B | 62.26 | 10.45 | 30.3 | 62.99 | 65.17 | 36.38 | 28.33 |
The following hyperparameters were used during training: