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README.md

@@ -1,41 +1,16 @@
 ---
 license: mit
 library_name: transformers
-base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
 tags:
 - llama-cpp
 - gguf-my-repo
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
 ---
 
 # Triangle104/DeepSeek-R1-Distill-Qwen-14B-Q4_K_M-GGUF
 This model was converted to GGUF format from [`deepseek-ai/DeepSeek-R1-Distill-Qwen-14B`](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B) for more details on the model.
 
----
-Model details:
--
-We introduce our first-generation reasoning models, DeepSeek-R1-Zero 
-and DeepSeek-R1. 
-DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning
- (RL) without supervised fine-tuning (SFT) as a preliminary step, 
-demonstrated remarkable performance on reasoning.
-With RL, DeepSeek-R1-Zero naturally emerged with numerous powerful and 
-interesting reasoning behaviors.
-However, DeepSeek-R1-Zero encounters challenges such as endless 
-repetition, poor readability, and language mixing. To address these 
-issues and further enhance reasoning performance,
-we introduce DeepSeek-R1, which incorporates cold-start data before RL.
-DeepSeek-R1 achieves performance comparable to OpenAI-o1 across math, 
-code, and reasoning tasks. 
-To support the research community, we have open-sourced 
-DeepSeek-R1-Zero, DeepSeek-R1, and six dense models distilled from 
-DeepSeek-R1 based on Llama and Qwen. DeepSeek-R1-Distill-Qwen-32B 
-outperforms OpenAI-o1-mini across various benchmarks, achieving new 
-state-of-the-art results for dense models.
-
-NOTE: Before running DeepSeek-R1 series models locally, we kindly recommend reviewing the Usage Recommendation section.
-
----
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)