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README.md
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1 |
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---
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language:
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- en
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- zh
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- id
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- th
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- vi
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- ms
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- lo
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datasets:
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- cerebras/SlimPajama-627B
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- Skywork/SkyPile-150B
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- allenai/MADLAD-400
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- cc100
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tags:
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- multilingual
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- sea
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- sailor
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- llama-cpp
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- gguf-my-repo
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license: apache-2.0
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base_model: sail/Sailor-7B
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model-index:
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- name: Sailor-7B
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results:
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- task:
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type: text-generation
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dataset:
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name: XQuAD-Thai
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type: XQuAD-Thai
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metrics:
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- type: EM (3-Shot)
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value: 57.88
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name: EM (3-Shot)
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- type: F1 (3-Shot)
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value: 71.06
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name: F1 (3-Shot)
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- task:
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type: text-generation
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dataset:
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name: TyDiQA-Indonesian
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type: TyDiQA-Indonesian
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metrics:
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- type: EM (3-Shot)
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value: 60.53
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name: EM (3-Shot)
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- type: F1 (3-Shot)
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value: 75.42
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name: F1 (3-Shot)
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- task:
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type: text-generation
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dataset:
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name: XQuAD-Vietnamese
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type: XQuAD-Vietnamese
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metrics:
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- type: EM (3-Shot)
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value: 53.81
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name: EM (3-Shot)
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- type: F1 (3-Shot)
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value: 74.62
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name: F1 (3-Shot)
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+
- task:
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type: text-generation
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dataset:
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name: XCOPA-Thai
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type: XCOPA-Thai
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metrics:
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68 |
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- type: EM (3-Shot)
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value: 59.0
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name: EM (3-Shot)
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- task:
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type: text-generation
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dataset:
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name: XCOPA-Indonesian
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type: XCOPA-Indonesian
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metrics:
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- type: EM (3-Shot)
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value: 72.2
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name: EM (3-Shot)
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- task:
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type: text-generation
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dataset:
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name: XCOPA-Vietnamese
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type: XCOPA-Vietnamese
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metrics:
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- type: EM (3-Shot)
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value: 72.2
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name: EM (3-Shot)
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- task:
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type: text-generation
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dataset:
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name: M3Exam-Thai
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type: M3Exam-Thai
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metrics:
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- type: EM (3-Shot)
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value: 30.0
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name: EM (3-Shot)
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- task:
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type: text-generation
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dataset:
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name: M3Exam-Indonesian
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type: M3Exam-Indonesian
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metrics:
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- type: EM (3-Shot)
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value: 32.88
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name: EM (3-Shot)
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- task:
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type: text-generation
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dataset:
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name: M3Exam-Vietnamese
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type: M3Exam-Vietnamese
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metrics:
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- type: EM (3-Shot)
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value: 44.1
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name: EM (3-Shot)
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- task:
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type: text-generation
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dataset:
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name: BELEBELE-Thai
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type: BELEBELE-Thai
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metrics:
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- type: EM (3-Shot)
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value: 41.56
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name: EM (3-Shot)
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- task:
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type: text-generation
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dataset:
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name: BELEBELE-Indonesian
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type: BELEBELE-Indonesian
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metrics:
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- type: EM (3-Shot)
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value: 44.33
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name: EM (3-Shot)
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- task:
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type: text-generation
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136 |
+
dataset:
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name: BELEBELE-Vietnamese
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138 |
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type: BELEBELE-Vietnamese
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139 |
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metrics:
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- type: EM (3-Shot)
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value: 45.33
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name: EM (3-Shot)
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---
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# AIronMind/Sailor-7B-Q4_K_M-GGUF
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This model was converted to GGUF format from [`sail/Sailor-7B`](https://huggingface.co/sail/Sailor-7B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/sail/Sailor-7B) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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```bash
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brew install llama.cpp
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```
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Invoke the llama.cpp server or the CLI.
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### CLI:
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```bash
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llama-cli --hf-repo AIronMind/Sailor-7B-Q4_K_M-GGUF --hf-file sailor-7b-q4_k_m.gguf -p "The meaning to life and the universe is"
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```
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### Server:
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```bash
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llama-server --hf-repo AIronMind/Sailor-7B-Q4_K_M-GGUF --hf-file sailor-7b-q4_k_m.gguf -c 2048
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```
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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.
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Step 1: Clone llama.cpp from GitHub.
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```
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git clone https://github.com/ggerganov/llama.cpp
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```
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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).
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```
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cd llama.cpp && LLAMA_CURL=1 make
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```
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Step 3: Run inference through the main binary.
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```
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./llama-cli --hf-repo AIronMind/Sailor-7B-Q4_K_M-GGUF --hf-file sailor-7b-q4_k_m.gguf -p "The meaning to life and the universe is"
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```
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or
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```
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./llama-server --hf-repo AIronMind/Sailor-7B-Q4_K_M-GGUF --hf-file sailor-7b-q4_k_m.gguf -c 2048
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```
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