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README.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- LLMs
+- mistral
+- math
+- Intel
+- llama-cpp
+- gguf-my-repo
+base_model: Intel/neural-chat-7b-v3-2
+datasets:
+- meta-math/MetaMathQA
+model-index:
+- name: neural-chat-7b-v3-2
+  results:
+  - task:
+      type: Large Language Model
+      name: Large Language Model
+    dataset:
+      name: meta-math/MetaMathQA
+      type: meta-math/MetaMathQA
+    metrics:
+    - type: ARC (25-shot)
+      value: 67.49
+      name: ARC (25-shot)
+      verified: true
+    - type: HellaSwag (10-shot)
+      value: 83.92
+      name: HellaSwag (10-shot)
+      verified: true
+    - type: MMLU (5-shot)
+      value: 63.55
+      name: MMLU (5-shot)
+      verified: true
+    - type: TruthfulQA (0-shot)
+      value: 59.68
+      name: TruthfulQA (0-shot)
+      verified: true
+    - type: Winogrande (5-shot)
+      value: 79.95
+      name: Winogrande (5-shot)
+      verified: true
+    - type: GSM8K (5-shot)
+      value: 55.12
+      name: GSM8K (5-shot)
+      verified: true
+---
+
+# DarkJanissary/neural-chat-7b-v3-2-Q6_K-GGUF
+This model was converted to GGUF format from [`Intel/neural-chat-7b-v3-2`](https://huggingface.co/Intel/neural-chat-7b-v3-2) 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/Intel/neural-chat-7b-v3-2) for more details on the model.
+
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
+
+```bash
+brew install llama.cpp
+
+```
+Invoke the llama.cpp server or the CLI.
+
+### CLI:
+```bash
+llama --hf-repo DarkJanissary/neural-chat-7b-v3-2-Q6_K-GGUF --hf-file neural-chat-7b-v3-2-q6_k.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo DarkJanissary/neural-chat-7b-v3-2-Q6_K-GGUF --hf-file neural-chat-7b-v3-2-q6_k.gguf -c 2048
+```
+
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+
+Step 1: Clone llama.cpp from GitHub.
+```
+git clone https://github.com/ggerganov/llama.cpp
+```
+
+Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
+```
+cd llama.cpp && LLAMA_CURL=1 make
+```
+
+Step 3: Run inference through the main binary.
+```
+./main --hf-repo DarkJanissary/neural-chat-7b-v3-2-Q6_K-GGUF --hf-file neural-chat-7b-v3-2-q6_k.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./server --hf-repo DarkJanissary/neural-chat-7b-v3-2-Q6_K-GGUF --hf-file neural-chat-7b-v3-2-q6_k.gguf -c 2048
+```