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README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+inference: false 
+base_model: Qwen/Qwen2.5-14B-Instruct
+base_model_relation: quantized 
+tags: [green, llmware-chat, p14, gguf,emerald]
+---
+
+# qwen2.5-14b-instruct-gguf
+
+**qwen2.5-14b-instruct-gguf** is a GGUF Q4_K_M int4 quantized version of [Qwen2.5-14B-Instruct](https://www.huggingface.co/Qwen/Qwen2.5-14B-Instruct), providing a very fast inference implementation, optimized for AI PCs.    
+
+This is from the latest release series from Qwen, and is one of the largest models in the collection.   
+
+This model will run on an AI PC, with GPU acceleration and 32 GB of memory.   Please note that the loading can take a little bit of time, but inference is still quite fast.  
+
+
+### Model Description
+
+- **Developed by:** Qwen
+- **Model type:** qwen2.5
+- **Parameters:** 14 billion  
+- **Model Parent:** Qwen/Qwen2.5-14B-Instruct  
+- **Language(s) (NLP):** English  
+- **License:** Apache 2.0  
+- **Uses:** Chat, general-purpose LLM  
+- **Quantization:** int4  
+  
+
+## Model Card Contact  
+
+[llmware on github](https://www.github.com/llmware-ai/llmware) 
+
+[llmware on hf](https://www.huggingface.co/llmware)  
+
+[llmware website](https://www.llmware.ai)  

config.json

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+{
+  "_name_or_path": "Qwen/Qwen2.5-14B-Instruct",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 13824,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 70,
+  "model_type": "qwen2",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.2",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

hash_record_sha256.json

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+{
+ "Qwen2.5-14B-Instruct-Q4_K_M.gguf": "e47ad95dad6ff848b431053b375adb5d39321290ea2c638682577dafca87c008",
+ "time_stamp": "2025-02-09_064024"
+}