commit cb316fc1ed1b239c8de4061476701257a10a12b1 Author: ModelHub XC Date: Mon Aug 10 03:01:16 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: Yoro9381/LFM2.5-1.2B-Instruct-Korean-Opus-4.6-Distill-GGUF Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..081463b --- /dev/null +++ b/.gitattributes @@ -0,0 +1,39 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs 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filter=lfs diff=lfs merge=lfs -text +model-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text +model-f16.gguf filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..0d04afc --- /dev/null +++ b/README.md @@ -0,0 +1,114 @@ +--- +base_model: Yoro9381/LFM2.5-1.2B-Instruct-Korean-Opus-4.6-Distill +library_name: transformers +pipeline_tag: text-generation +license: other +license_name: lfm-open-license-v1.0 +license_link: https://huggingface.co/LiquidAI/LFM2.5-1.2B-Instruct/blob/main/LICENSE +tags: +- unsloth +- lfm2 +- lfm2.5 +- korean +- text-generation +- conversational +- instruction-tuned +datasets: +- Jongsim/claude-opus-4.6-reasoning-12k-ko-filtered-v2 +language: +- ko +--- +# LFM2.5-1.2B-Instruct-Korean + +## Model Overview + +`LFM2.5-1.2B-Instruct-Korean` is a Korean instruction-following language model based on `LiquidAI/LFM2.5-1.2B-Instruct`. +This model was fine-tuned on Korean-centered datasets with the goal of improving performance on Korean question answering, general conversation, and instruction-following tasks. + +The model is designed to generate responses that are more natural, consistent, and contextually appropriate in Korean. + +## Base Model + +- **Base model**: `LiquidAI/LFM2.5-1.2B-Instruct` + +## Training Data + +This model was fine-tuned using the following Korean-centered datasets: + +- `maywell/koVast` +- `CarrotAI/ko-instruction-dataset` +- `MarkrAI/KoCommercial-Dataset` +- `Jongsim/claude-opus-4.6-reasoning-12k-ko-filtered-v2` + +The training data includes Korean instruction-response pairs, general conversational data, and commercially or practically oriented text. +This setup was intended to help the model learn a broad range of Korean expressions, styles, and contexts. + +## Training Details + +The model was trained for **3 full epochs** over the entire dataset. +Training proceeded for a total of **2,160 steps** and was completed successfully without interruption. + +### Training Summary + +- **Number of epochs**: 3 +- **Total training steps**: 2,160 +- **Training completion status**: Completed +- **Training status**: Stable + +## Evaluation Results + +The final evaluation metrics are as follows: + +- **training_loss**: 0.9999 +- **eval_loss**: 1.0480 +- **eval_mean_token_accuracy**: 0.7445 + +These results show that the training loss and evaluation loss remained at nearly the same level, suggesting that the model demonstrated relatively stable generalization performance on the validation set without a clear sign of overfitting. + +## Result Interpretation + +One notable point in this experiment is the very small gap between **training loss** and **evaluation loss**. + +- **training_loss = 0.9999** +- **eval_loss = 1.0480** + +In general, a large gap between these two values may indicate overfitting. +However, in this experiment, the difference was very small, which suggests that the model adapted to the training data in a stable manner while maintaining a similar level of performance on the validation set. + +In addition, the result of **eval_mean_token_accuracy = 0.7445** indicates that the model predicts the next token in a relatively stable and consistent way. +Taken together, these results suggest that the model successfully learned the major patterns in the training data and converged stably without severe instability. + +## Overall Conclusion + +This fine-tuning was completed successfully and showed overall solid results. +The close alignment between training loss and evaluation loss suggests that the model did not significantly overfit during training and that the optimization process remained stable. + +Moreover, no sharp divergence in loss values was observed throughout the training process. +Therefore, this experiment can be regarded as a fine-tuning run that converged stably overall. + +## Limitations and Future Work + +While these metrics are useful for assessing training stability and convergence, they do not fully reflect response quality, factuality, instruction-following accuracy, or real-world usability. + +To obtain a more comprehensive evaluation of the model, the following additional assessments are planned: + +- evaluation on real user question-answer examples +- downstream task performance evaluation +- qualitative analysis of generated responses +- safety and hallucination checks + +Through these follow-up evaluations, we aim to verify whether the model can go beyond stable training-time metrics and provide reliable and consistent performance in real-world usage scenarios. + +## License + +This model is a fine-tuned derivative of `LiquidAI/LFM2.5-1.2B-Instruct`. + +Use and distribution of this model are subject to the terms of the **LFM Open License v1.0** applicable to the base model. + +Please also review any additional obligations arising from the datasets used during fine-tuning. + +## Feedback + +This model will continue to be improved through further evaluation and refinement. +If you have any feedback on your experience using the model or notice areas that need improvement, your input will be carefully considered and reflected in future quality improvements. +Your feedback will be a great source of support in improving and further developing the model. \ No newline at end of file diff --git a/model-Q4_K_M.gguf b/model-Q4_K_M.gguf new file mode 100644 index 0000000..40a02c3 --- /dev/null +++ b/model-Q4_K_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cb988bfb41b8c5e2037ae0d192e51a6776b13f118a9b6afa03fd734859485df5 +size 730894688 diff --git a/model-Q5_K_M.gguf b/model-Q5_K_M.gguf new file mode 100644 index 0000000..6bfd690 --- /dev/null +++ b/model-Q5_K_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cf1e85f4f398719d47e5a09553a64712726012f65c65c0390450768d16716c8b +size 843354464 diff --git a/model-Q8_0.gguf b/model-Q8_0.gguf new file mode 100644 index 0000000..cf796fe --- /dev/null +++ b/model-Q8_0.gguf @@ -0,0 +1,3 @@ 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