--- base_model: unsloth/mistral-7b-instruct-v0.3-bnb-4bit tags: - text-generation-inference - transformers - unsloth - mistral - trl license: apache-2.0 datasets: - neph1/bellman-7b-finetune - neph1/bellman-multiturn language: - sv --- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/653cd3049107029eb004f968/pLcriXAfp3Y9Z0RGwwVUB.png) It's finetuned for prompt question answering, based on a dataset created from Swedish wikipedia, with a lot of Sweden-centric questions. New in this version is a multi-turn dataset of about 250 conversations, as well as a number of stories. The name comes from the Swedish bard and poet Carl Mikael Bellman who lived in the 1700s. As with any bard, what this model says should be taken with a grain of salt. Even though it has the best of intentions. [![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/T6T3S8VXY) Configuration: Rank: 256 Alpha: 512 Learning rate (at start): 2e-5 Context length: 4096 Training length: ca 2 epochs Important. Use correct prompt format for best results: ```[INST]Hur bakar jag en sockerkaka?[/INST]``` TrainingArguments( per_device_train_batch_size = 6, gradient_accumulation_steps = 20, num_train_epochs=4, warmup_steps = 10, learning_rate = 2e-5, bf16 = true, logging_steps = 5, optim = "adamw_8bit", weight_decay = 0.01, lr_scheduler_type = "linear", seed = 3407, per_device_eval_batch_size = 6, eval_strategy="steps", eval_accumulation_steps = 20, eval_steps = 5, eval_delay = 0, save_strategy="steps", save_steps=5, report_to="none", output_dir="", ) # Uploaded model - **Developed by:** neph1 - **License:** apache-2.0 - **Finetuned from model :** unsloth/mistral-7b-instruct-v0.3-bnb-4bit This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [](https://github.com/unslothai/unsloth)