cleanup

README.md

@@ -12,33 +12,26 @@ quantized_by: Nomic
 tags:
   - feature-extraction
   - sentence-similarity
+new_version: nomic-ai/nomic-embed-text-v1.5-GGUF
 ---
 
-***
-**Note**: For compatiblity with current llama.cpp, please download the files published on 2/15/2024. The files originally published here will fail to load.
-***
-
-<br/>
-
 # nomic-embed-text-v1 - GGUF
 
 Original model: [nomic-embed-text-v1](https://huggingface.co/nomic-ai/nomic-embed-text-v1)
 
 ## Usage
 
-Embedding text with `nomic-embed-text` requires task instruction prefixes at the beginning of each string. 
+Embedding text with `nomic-embed-text` requires task instruction prefixes at the beginning of each string.
 
 For example, the code below shows how to use the `search_query` prefix to embed user questions, e.g. in a RAG application.
 
-To see the full set of task instructions available & how they are designed to be used, visit the model card for [nomic-embed-text-v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5).
+To see the full set of task instructions available & how they are designed to be used, visit the model card for [nomic-embed-text-v1](https://huggingface.co/nomic-ai/nomic-embed-text-v1).
 
 ## Description
 
 This repo contains llama.cpp-compatible files for [nomic-embed-text-v1](https://huggingface.co/nomic-ai/nomic-embed-text-v1) in GGUF format.
 
-llama.cpp will default to 2048 tokens of context with these files. To use the full 8192 tokens that Nomic Embed is benchmarked on, you will have to choose a context extension method. The original model uses Dynamic NTK-Aware RoPE scaling, but that is not currently available in llama.cpp. A combination of YaRN and linear scaling is an acceptable substitute.
-
-These files were converted and quantized with llama.cpp [PR 5500](https://github.com/ggerganov/llama.cpp/pull/5500), commit [34aa045de](https://github.com/ggerganov/llama.cpp/pull/5500/commits/34aa045de44271ff7ad42858c75739303b8dc6eb).
+llama.cpp will default to 2048 tokens of context with these files. For the full 8192 token context length, you will have to choose a context extension method. The 🤗 Transformers model uses Dynamic NTK-Aware RoPE scaling, but that is not currently available in llama.cpp.
 
 ## Example `llama.cpp` Command