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README.md

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+---
+language:
+- en
+- fr
+- ru
+- de
+- ja
+- ko
+- zh
+- it
+- uk
+- multilingual
+- code
+license: apache-2.0
+library_name: transformers
+tags:
+- mistral
+- gistral
+- gistral-16b
+- multilingual
+- code
+- 128k
+- metamath
+- grok-1
+- anthropic
+- openhermes
+- instruct
+- merge
+- llama-cpp
+- gguf-my-repo
+base_model: ehristoforu/Gistral-16B
+datasets:
+- HuggingFaceH4/grok-conversation-harmless
+- HuggingFaceH4/ultrachat_200k
+- HuggingFaceH4/ultrafeedback_binarized_fixed
+- HuggingFaceH4/cai-conversation-harmless
+- meta-math/MetaMathQA
+- emozilla/yarn-train-tokenized-16k-mistral
+- snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
+- microsoft/orca-math-word-problems-200k
+- m-a-p/Code-Feedback
+- teknium/openhermes
+- lksy/ru_instruct_gpt4
+- IlyaGusev/ru_turbo_saiga
+- IlyaGusev/ru_sharegpt_cleaned
+- IlyaGusev/oasst1_ru_main_branch
+pipeline_tag: text-generation
+---
+
+# maria-ai/Gistral-16B-Q4_K_S-GGUF
+This model was converted to GGUF format from [`ehristoforu/Gistral-16B`](https://huggingface.co/ehristoforu/Gistral-16B) 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/ehristoforu/Gistral-16B) 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 maria-ai/Gistral-16B-Q4_K_S-GGUF --hf-file gistral-16b-q4_k_s.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo maria-ai/Gistral-16B-Q4_K_S-GGUF --hf-file gistral-16b-q4_k_s.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 maria-ai/Gistral-16B-Q4_K_S-GGUF --hf-file gistral-16b-q4_k_s.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./server --hf-repo maria-ai/Gistral-16B-Q4_K_S-GGUF --hf-file gistral-16b-q4_k_s.gguf -c 2048
+```