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RichardErkhov/ReBatch_-_Reynaerde-7B-Instruct-gguf
ReBatch_-_Reynaerde-7B-Instruct-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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.gguf92.3 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
Reynaerde-7B-Instruct - GGUF
| Name | Quant method | Size |
|---|---|---|
| Reynaerde-7B-Instruct.Q2_K.gguf | Q2_K | 2.54GB |
| Reynaerde-7B-Instruct.IQ3_XS.gguf | IQ3_XS | 2.82GB |
| Reynaerde-7B-Instruct.IQ3_S.gguf | IQ3_S | 0.17GB |
| Reynaerde-7B-Instruct.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| Reynaerde-7B-Instruct.IQ3_M.gguf | IQ3_M | 3.06GB |
| Reynaerde-7B-Instruct.Q3_K.gguf | Q3_K | 3.28GB |
| Reynaerde-7B-Instruct.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| Reynaerde-7B-Instruct.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| Reynaerde-7B-Instruct.IQ4_XS.gguf | IQ4_XS | 3.68GB |
| Reynaerde-7B-Instruct.Q4_0.gguf | Q4_0 | 3.83GB |
| Reynaerde-7B-Instruct.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| Reynaerde-7B-Instruct.Q4_K_S.gguf | Q4_K_S | 3.86GB |
| Reynaerde-7B-Instruct.Q4_K.gguf | Q4_K | 4.07GB |
| Reynaerde-7B-Instruct.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| Reynaerde-7B-Instruct.Q4_1.gguf | Q4_1 | 4.24GB |
| Reynaerde-7B-Instruct.Q5_0.gguf | Q5_0 | 4.66GB |
| Reynaerde-7B-Instruct.Q5_K_S.gguf | Q5_K_S | 4.66GB |
| Reynaerde-7B-Instruct.Q5_K.gguf | Q5_K | 4.78GB |
| Reynaerde-7B-Instruct.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| Reynaerde-7B-Instruct.Q5_1.gguf | Q5_1 | 5.07GB |
| Reynaerde-7B-Instruct.Q6_K.gguf | Q6_K | 5.54GB |
| Reynaerde-7B-Instruct.Q8_0.gguf | Q8_0 | 7.17GB |
license: apache-2.0 base_model: mistralai/Mistral-7B-v0.3 tags:
This model is a fine-tuned version of mistralai/Mistral-7B-v0.3-Instruct on the ReBatch/ultrachat_400k_nl, the BramVanroy/stackoverflow-chat-dutch and the BramVanroy/no_robots_dutch datasets.
This model is a Dutch chat model, originally developed from Mistral 7B v0.3 Instruct and further finetuned first with SFT on multiple datasets.
The model could generate wrong, misleading, and potentially even offensive content. Use at your own risk. Use with mistrals chat template.
It achieves the following results on the evaluation set:
This model was trained with QLoRa in bfloat16 with Flash Attention 2 on one A100 PCIe, using the sft script from the alignment handbook on RunPod.
The following hyperparameters were used during training:
The Mistral-7B-v0.3-Instruct model, on which this model is based, was created by Mistral AI. The finetuning was done by Julien Van den Avenne.