Update README.md

README.md

@@ -1,7 +1,7 @@
 ---
 language:
 - en
-license: apache-2.0
+license: cc-by-nc-4.0
 tags:
 - text-generation-inference
 - transformers
@@ -9,15 +9,28 @@ tags:
 - llama
 - trl
 - sft
+- Roleplay
+- roleplay
 base_model: Sao10K/Fimbulvetr-11B-v2
 ---
+# About this model
 
-# Uploaded  model
+Beta for V2 of https://huggingface.co/Alsebay/Narumashi-11B-v0.9 (wrong typo but I'm too lazy to fix), but have only 32 rank and 32 lora rank, which cause the model didn't learn well all dataset information, it just know basis information. Anyways, it good if your have a chinese, japanese prompt to trigger TSF content. Maybe not smart, I haven't test yet.
 
-- **Developed by:** Alsebay
-- **License:** apache-2.0
-- **Finetuned from model :** Sao10K/Fimbulvetr-11B-v2
+- **Finetuned from model :** Sao10K/Fimbulvetr-11B-v2 . Thank Sao10K a lot :)
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+## I have text and found that Sao10K/Fimbulvetr-11B-v2 could unlock as 8K context length (maybe logic will go down a bit?), so I leave it alone to reduce RAM and VRAM. That mean you can use as 8k context length although this model say only 4k.
+## GGUF version? [here is it](https://huggingface.co/Alsebay/Narisumashi-GGUF).
+## Dataset
+All chinese novels dataset
+```
+Dataset(all are novels):
+60% skinsuit
+25% possession
+5% transform(shapeshift)
+10% other
+```
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+# Thank Unsloth for good finetuning tool. This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)