Valheim Assistant V1 - 16-bit Version

This is a fine-tuned version of the Unsloth Phi-3.5-mini-instruct model. It is designed to provide conversational assistance for the game Valheim, covering gameplay mechanics, lore, and in-game strategies.

This model is part of an ongoing hobbyist project, created by a novice enthusiast exploring fine-tuning techniques. While the dataset and model may have limitations, this project aims to improve over time through community feedback and iteration.


Model Details

Summary

This model has been fine-tuned on Egrigor/ValheimTestData, which contains conversational-style question-and-answer pairs derived from Valheim community resources.


How to Use

To load and interact with the model, use the following code:

from unsloth import FastLanguageModel from transformers import AutoTokenizer

Load model and tokenizer

model = FastLanguageModel.from_pretrained("Egrigor/ValheimAssistantV1-16bit") tokenizer = AutoTokenizer.from_pretrained("Egrigor/ValheimAssistantV1-16bit")

Prepare input and generate output

inputs = tokenizer("How do I build a crafting station?", return_tensors="pt") outputs = model.generate(**inputs, max_length=100)

Decode and print the output

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Training Details

Framework: Unsloth

Batch Size per Device: 2

Gradient Accumulation Steps: 4

Learning Rate: 2e-4

Total Training Steps: 60

Training Time: ~3.5 minutes

Dataset

The dataset consists of gameplay tips, lore insights, and strategic guidance, formatted into conversational question-and-answer pairs.

Note: As this dataset was semi-automatically generated from community resources, it may contain inaccuracies or gaps. Feedback is welcome for future improvements.

Limitations and Future Work

Dataset Gaps: The dataset may not fully cover Valheims gameplay and lore, and some responses may be incomplete or inaccurate.

Generalization: This model is focused solely on Valheim-related content and may not perform well in other contexts.

Iterative Improvement: Future versions will refine the dataset and model based on testing and community feedback.

Contact and Feedback

This is an experimental project created by a novice AI enthusiast. Feedback, suggestions, and collaborations are highly welcome! Feel free to reach out via Hugging Face.


Let me know if there’s anything specific you’d like to tweak or emphasize!

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