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HelpingAI2.5-5B-GGUF

Text Generation
Transformers
GGUF
English
HelpingAI
Emotionally-Intelligent
EQ-focused
Conversational
SLM
llama-cpp
matrixportal
conversational
Model card Files
xet
Community
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@@ -14,49 +14,30 @@ tags:
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  - Conversational
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  - SLM
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  - llama-cpp
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- - gguf-my-repo
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  ---
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  # ysn-rfd/HelpingAI2.5-5B-GGUF
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- This model was converted to GGUF format from [`HelpingAI/HelpingAI2.5-5B`](https://huggingface.co/HelpingAI/HelpingAI2.5-5B) 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/HelpingAI/HelpingAI2.5-5B) 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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-
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- ```bash
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- brew install llama.cpp
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-
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- ```
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- Invoke the llama.cpp server or the CLI.
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-
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- ### CLI:
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- ```bash
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- llama-cli --hf-repo ysn-rfd/HelpingAI2.5-5B-GGUF --hf-file helpingai2.5-5b-q5_0.gguf -p "The meaning to life and the universe is"
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- ```
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-
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- ### Server:
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- ```bash
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- llama-server --hf-repo ysn-rfd/HelpingAI2.5-5B-GGUF --hf-file helpingai2.5-5b-q5_0.gguf -c 2048
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- ```
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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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-
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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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-
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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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-
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- Step 3: Run inference through the main binary.
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- ```
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- ./llama-cli --hf-repo ysn-rfd/HelpingAI2.5-5B-GGUF --hf-file helpingai2.5-5b-q5_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 ysn-rfd/HelpingAI2.5-5B-GGUF --hf-file helpingai2.5-5b-q5_0.gguf -c 2048
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- ```
 
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  - Conversational
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  - SLM
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  - llama-cpp
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+ - matrixportal
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  ---
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  # ysn-rfd/HelpingAI2.5-5B-GGUF
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+ This model was converted to GGUF format from [`HelpingAI/HelpingAI2.5-5B`](https://huggingface.co/HelpingAI/HelpingAI2.5-5B) using llama.cpp via the ggml.ai's [all-gguf-same-where](https://huggingface.co/spaces/matrixportal/all-gguf-same-where) space.
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  Refer to the [original model card](https://huggingface.co/HelpingAI/HelpingAI2.5-5B) for more details on the model.
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+ ## ✅ Quantized Models Download List
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+ **✨ Recommended for CPU:** `Q4_K_M` | **⚡ Recommended for ARM CPU:** `Q4_0` | **🏆 Best Quality:** `Q8_0`
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+
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+ | 🚀 Download | 🔢 Type | 📝 Notes |
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+ |:---------|:-----|:------|
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q2_k.gguf) | ![Q2_K](https://img.shields.io/badge/Q2_K-1A73E8) | Basic quantization |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q3_k_s.gguf) | ![Q3_K_S](https://img.shields.io/badge/Q3_K_S-34A853) | Small size |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q3_k_m.gguf) | ![Q3_K_M](https://img.shields.io/badge/Q3_K_M-FBBC05) | Balanced quality |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q3_k_l.gguf) | ![Q3_K_L](https://img.shields.io/badge/Q3_K_L-4285F4) | Better quality |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q4_0.gguf) | ![Q4_0](https://img.shields.io/badge/Q4_0-EA4335) | Fast on ARM |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q4_k_s.gguf) | ![Q4_K_S](https://img.shields.io/badge/Q4_K_S-673AB7) | Fast, recommended |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q4_k_m.gguf) | ![Q4_K_M](https://img.shields.io/badge/Q4_K_M-673AB7) ⭐ | Best balance |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q5_0.gguf) | ![Q5_0](https://img.shields.io/badge/Q5_0-FF6D01) | Good quality |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q5_k_s.gguf) | ![Q5_K_S](https://img.shields.io/badge/Q5_K_S-0F9D58) | Balanced |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q5_k_m.gguf) | ![Q5_K_M](https://img.shields.io/badge/Q5_K_M-0F9D58) | High quality |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q6_k.gguf) | ![Q6_K](https://img.shields.io/badge/Q6_K-4285F4) 🏆 | Very good quality |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-q8_0.gguf) | ![Q8_0](https://img.shields.io/badge/Q8_0-EA4335) ⚡ | Fast, best quality |
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+ | [Download](https://huggingface.co/ysn-rfd/HelpingAI2.5-5B-GGUF/resolve/main/helpingai2.5-5b-f16.gguf) | ![F16](https://img.shields.io/badge/F16-000000) | Maximum accuracy |
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+
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+ 💡 **Tip:** Use `F16` for maximum precision when quality is critical