Update README.md

README.md

@@ -1,50 +1,46 @@
 ---
-base_model: []
-library_name: transformers
+license: apache-2.0
+language:
+- en
+- ja
 tags:
-- mergekit
-- merge
-
+- finetuned
+library_name: transformers
+pipeline_tag: text-generation
 ---
-# dump
-
-This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
-
-## Merge Details
-### Merge Method
-
-This model was merged using the [linear](https://arxiv.org/abs/2203.05482) merge method.
-
-### Models Merged
-
-The following models were included in the merge:
-* /home/ubuntu/work/Exveria/text-generation-webui/models/Ninja-v1
-* /home/ubuntu/work/Umise/TGenwebui/models/VT4o3
-* /home/ubuntu/work/Umise/TGenwebui/models/VT3
-* /home/ubuntu/work/Umise/TGenwebui/models/VT4
-* /home/ubuntu/work/Exveria/text-generation-webui/models/Ninja-32k-NSFW
-
-### Configuration
-
-The following YAML configuration was used to produce this model:
-
-```yaml
-models:
-  - model: /home/ubuntu/work/Exveria/text-generation-webui/models/Ninja-32k-NSFW
-    parameters:
-      weight: 0.6
-  - model: /home/ubuntu/work/Umise/TGenwebui/models/VT4o3
-    parameters:
-      weight: 1
-  - model: /home/ubuntu/work/Exveria/text-generation-webui/models/Ninja-v1
-    parameters:
-      weight: 0.6
-  - model: /home/ubuntu/work/Umise/TGenwebui/models/VT3
-    parameters:
-      weight: 1
-  - model: /home/ubuntu/work/Umise/TGenwebui/models/VT4
-    parameters:
-      weight: 0.6
-merge_method: linear
-dtype: bfloat16
-```
+
+# Model Card for VecTeus-v1.0
+
+The Mistral-7B--based Large Language Model (LLM) is an noveldataset fine-tuned version of the Mistral-7B-v0.1
+
+VecTeus has the following changes compared to Mistral-7B-v0.1.
+- 128k context window (8k context in v0.1)
+- Achieving both high quality Japanese and English generation
+- Can be generated NSFW
+- Memory ability that does not forget even after long-context generation
+
+This model was created with the help of GPUs from the first LocalAI hackathon.
+
+We would like to take this opportunity to thank
+
+## List of Creation Methods
+
+- Chatvector for multiple models
+- Simple linear merging of result models
+- Domain and Sentence Enhancement with LORA
+- Context expansion
+
+## Instruction format
+
+  Freed from templates. Congratulations
+
+## Example prompts to improve (Japanese)
+
+  - BAD:　あなたは○○として振る舞います
+  - GOOD: あなたは○○です
+
+  - BAD: あなたは○○ができます
+  - GOOD: あなたは○○をします
+
+# Other points to keep in mind
+  If possible, we recommend inferring with llamacpp rather than Transformers.