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--- |
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base_model: FuseAI/FuseChat-Qwen-2.5-7B-Instruct |
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tags: |
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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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--- |
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# Triangle104/FuseChat-Qwen-2.5-7B-Instruct-Q8_0-GGUF |
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This model was converted to GGUF format from [`FuseAI/FuseChat-Qwen-2.5-7B-Instruct`](https://huggingface.co/FuseAI/FuseChat-Qwen-2.5-7B-Instruct) 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/FuseAI/FuseChat-Qwen-2.5-7B-Instruct) for more details on the model. |
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--- |
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transferring capabilities from source LLMs to a target LLM. First, |
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during dataset construction, we sample N responses from |
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each of the source LLMs and annotate these responses using an external |
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reward model. Second, in the supervised fine-tuning (SFT) |
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stage, we fine-tune the target model using the best responses, which |
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not only enhances the target model's capabilities but also helps |
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mitigate the distributional gap between the source and target models. |
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Finally, in the direct preference optimization (DPO) |
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stage, we optimize the target model by using the best and worst |
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responses from the source models as preference pairs, further enhancing |
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the target model's performance. The complete pipeline will be detailed |
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in the following paragraph. |
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Dataset |
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Prompt Selection |
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Our datasets were designed to enhance model's instruction following, |
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general conversation, mathematics, coding, and Chinese-language |
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capabilities. We selected data from open-source community datasets, |
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applying targeted filtering and preprocessing. Key datasets and |
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filtering criteria included: |
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Instruction Following & General Conversation: Sourced from UltraFeedback, Magpie-Pro-DPO-100K-v0.1, and HelpSteer2, excluding code and math data. |
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Mathematics: Selected from OpenMathInstruct-2, with nearly 60,000 unique samples. |
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Coding: Curated from leetcode and self-oss-instruct-sc2-exec-filter-50k, retaining prompts with test cases. |
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Chinese Language: Integrated alpaca_gpt4_zh and Magpie-Qwen2-Pro-200K-Chinese, filtering out code and math prompts to retain approximately 10,000 high-quality samples. |
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Response Sampling |
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For each dataset's prompts, we synthesized responses mainly from four different series of source models, specifically Gemma-2-27b-It, Mistral-Large-Instruct-2407, Qwen-2.5-72B-Instruct, and Llama-3.1-70B-Instruct. |
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Instruction Following & General Conversation: We sampled each prompt five times from all the source models. |
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Mathematics: We retained the responses generated by |
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Llama-3.1-405B-Instruct from the original dataset (OpenMathInstruct-2) |
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and additionally sampled responses using Qwen-2.5-Math-72B-Instruct. |
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Coding: We sampled each prompt eight times for all source models. |
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Chinese Language: We included single response sampled exclusively from Qwen-2.5-72B-Instruct. |
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--- |
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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 Triangle104/FuseChat-Qwen-2.5-7B-Instruct-Q8_0-GGUF --hf-file fusechat-qwen-2.5-7b-instruct-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 Triangle104/FuseChat-Qwen-2.5-7B-Instruct-Q8_0-GGUF --hf-file fusechat-qwen-2.5-7b-instruct-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 Triangle104/FuseChat-Qwen-2.5-7B-Instruct-Q8_0-GGUF --hf-file fusechat-qwen-2.5-7b-instruct-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 Triangle104/FuseChat-Qwen-2.5-7B-Instruct-Q8_0-GGUF --hf-file fusechat-qwen-2.5-7b-instruct-q8_0.gguf -c 2048 |
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``` |
