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README.md

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+---
+language:
+- en
+- zh
+- id
+- th
+- vi
+- ms
+- lo
+datasets:
+- cerebras/SlimPajama-627B
+- Skywork/SkyPile-150B
+- allenai/MADLAD-400
+- cc100
+tags:
+- multilingual
+- sea
+- sailor
+- llama-cpp
+- gguf-my-repo
+license: apache-2.0
+base_model: sail/Sailor-1.8B
+inference: false
+model-index:
+- name: Sailor-1.8B
+  results:
+  - task:
+      type: text-generation
+    dataset:
+      name: XQuAD-Thai
+      type: XQuAD-Thai
+    metrics:
+    - type: EM (3-Shot)
+      value: 32.72
+      name: EM (3-Shot)
+    - type: F1 (3-Shot)
+      value: 48.66
+      name: F1 (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: TyDiQA-Indonesian
+      type: TyDiQA-Indonesian
+    metrics:
+    - type: EM (3-Shot)
+      value: 40.88
+      name: EM (3-Shot)
+    - type: F1 (3-Shot)
+      value: 65.37
+      name: F1 (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: XQuAD-Vietnamese
+      type: XQuAD-Vietnamese
+    metrics:
+    - type: EM (3-Shot)
+      value: 34.22
+      name: EM (3-Shot)
+    - type: F1 (3-Shot)
+      value: 53.35
+      name: F1 (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: XCOPA-Thai
+      type: XCOPA-Thai
+    metrics:
+    - type: EM (3-Shot)
+      value: 53.8
+      name: EM (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: XCOPA-Indonesian
+      type: XCOPA-Indonesian
+    metrics:
+    - type: EM (3-Shot)
+      value: 64.2
+      name: EM (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: XCOPA-Vietnamese
+      type: XCOPA-Vietnamese
+    metrics:
+    - type: EM (3-Shot)
+      value: 63.2
+      name: EM (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: M3Exam-Thai
+      type: M3Exam-Thai
+    metrics:
+    - type: EM (3-Shot)
+      value: 25.38
+      name: EM (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: M3Exam-Indonesian
+      type: M3Exam-Indonesian
+    metrics:
+    - type: EM (3-Shot)
+      value: 28.3
+      name: EM (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: M3Exam-Vietnamese
+      type: M3Exam-Vietnamese
+    metrics:
+    - type: EM (3-Shot)
+      value: 34.71
+      name: EM (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: BELEBELE-Thai
+      type: BELEBELE-Thai
+    metrics:
+    - type: EM (3-Shot)
+      value: 34.22
+      name: EM (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: BELEBELE-Indonesian
+      type: BELEBELE-Indonesian
+    metrics:
+    - type: EM (3-Shot)
+      value: 34.89
+      name: EM (3-Shot)
+  - task:
+      type: text-generation
+    dataset:
+      name: BELEBELE-Vietnamese
+      type: BELEBELE-Vietnamese
+    metrics:
+    - type: EM (3-Shot)
+      value: 35.33
+      name: EM (3-Shot)
+---
+
+# AIronMind/Sailor-1.8B-Q4_K_M-GGUF
+This model was converted to GGUF format from [`sail/Sailor-1.8B`](https://huggingface.co/sail/Sailor-1.8B) 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/sail/Sailor-1.8B) 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-cli --hf-repo AIronMind/Sailor-1.8B-Q4_K_M-GGUF --hf-file sailor-1.8b-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo AIronMind/Sailor-1.8B-Q4_K_M-GGUF --hf-file sailor-1.8b-q4_k_m.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.
+```
+./llama-cli --hf-repo AIronMind/Sailor-1.8B-Q4_K_M-GGUF --hf-file sailor-1.8b-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo AIronMind/Sailor-1.8B-Q4_K_M-GGUF --hf-file sailor-1.8b-q4_k_m.gguf -c 2048
+```