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README.md
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1 |
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---
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base_model: Ba2han/Llama-Phi-3_DoRA
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datasets:
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- Sao10K/Claude-3-Opus-Instruct-15K
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- abacusai/SystemChat-1.1
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- Ba2han/DollyLlama-5k
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language:
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- en
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license: mit
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tags:
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- llama-cpp
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- gguf-my-repo
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model-index:
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- name: Llama-Phi-3_DoRA
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 62.29
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 79.08
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 69.44
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 54.08
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 73.4
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 68.01
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
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name: Open LLM Leaderboard
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---
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# Stark2008/Llama-Phi-3_DoRA-Q8_0-GGUF
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This model was converted to GGUF format from [`Ba2han/Llama-Phi-3_DoRA`](https://huggingface.co/Ba2han/Llama-Phi-3_DoRA) 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/Ba2han/Llama-Phi-3_DoRA) 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 Stark2008/Llama-Phi-3_DoRA-Q8_0-GGUF --hf-file llama-phi-3_dora-q8_0.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 Stark2008/Llama-Phi-3_DoRA-Q8_0-GGUF --hf-file llama-phi-3_dora-q8_0.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 Stark2008/Llama-Phi-3_DoRA-Q8_0-GGUF --hf-file llama-phi-3_dora-q8_0.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 Stark2008/Llama-Phi-3_DoRA-Q8_0-GGUF --hf-file llama-phi-3_dora-q8_0.gguf -c 2048
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```
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