Update README.md

README.md

@@ -5,48 +5,32 @@ base_model:
 - adowu/a2
 library_name: transformers
 tags:
-- mergekit
-- merge
-
+- astral
+- 128k
+license: apache-2.0
+language:
+- en
 ---
-# merge
-
-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 [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [adowu/a2](https://huggingface.co/adowu/a2) as a base.
-
-### Models Merged
-
-The following models were included in the merge:
-* [adowu/a3](https://huggingface.co/adowu/a3)
-* [adowu/a1](https://huggingface.co/adowu/a1)
-
-### Configuration
-
-The following YAML configuration was used to produce this model:
-
-```yaml
-models:
-  - model: adowu/a1
-    parameters:
-      density: 1.0
-      weight: 0.9
-  - model: adowu/a2
-    parameters:
-      density: 1.0
-      weight: 1.0
-  - model: adowu/a3
-    parameters:
-      density: 1.0
-      weight: 0.8
-merge_method: dare_ties
-base_model: adowu/a2
-parameters:
-  normalize: true
-  int8_mask: true
-  temperature: 0.7
-dtype: bfloat16
-```
+
+# ASTRAL-128K
+
+### Model Description
+
+The adowu/astral-128k model is a state-of-the-art language model based on the MistralForCausalLM architecture, designed for causal text generation. This means the model generates text sequentially, where each subsequent word is chosen based on the previous words in the sequence. Below is an overview of the key features and configuration of this model.
+
+## Architectural Highlights
+The model is built on a foundation designed to understand and generate language by sequentially predicting the next piece of text based on the preceding context. Its architecture allows for deep understanding of language nuances, enabling the generation of text that is not only relevant but also rich in variety.
+
+## Capabilities
+With its advanced architecture, the model can handle a wide range of language generation tasks. It is capable of generating long passages of text that maintain coherence and relevance throughout, making it suitable for tasks such as content creation, conversation generation, and more complex applications like summarization and translation in context-rich scenarios.
+
+## Performance and Efficiency
+The model is optimized for both performance and efficiency, ensuring that it can process and generate text quickly while maintaining a high level of accuracy and coherence in the output. This balance makes it an excellent tool for developers and researchers looking for a reliable model for generating high-quality text.
+
+## Application Scope
+Due to its versatile nature, the model finds applications across various domains, including but not limited to, automated storytelling, chatbots, and assistance systems, content generation for websites, and aiding in the creation of written content for educational and informational purposes.
+
+In summary, the adowu/astral-128k model represents a significant advancement in the field of natural language processing, offering a powerful tool for generating human-like text across a wide array of applications.
+
+- **Developed by:** aww
+- **Model type:** Mistral