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--- |
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base_model: Salesforce/xLAM-8x7b-r |
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datasets: |
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- Salesforce/xlam-function-calling-60k |
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extra_gated_button_content: Agree and access repository |
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extra_gated_heading: Acknowledge to follow corresponding license to access the repository |
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inference: false |
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language: |
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- en |
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library_name: gguf |
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license: cc-by-nc-4.0 |
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pipeline_tag: text-generation |
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quantized_by: legraphista |
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tags: |
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- function-calling |
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- LLM Agent |
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- tool-use |
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- mistral |
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- pytorch |
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- quantized |
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- GGUF |
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- quantization |
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- imat |
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- imatrix |
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- static |
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- 16bit |
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- 8bit |
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- 6bit |
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- 5bit |
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- 4bit |
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- 3bit |
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- 2bit |
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- 1bit |
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--- |
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# xLAM-8x7b-r-IMat-GGUF |
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_Llama.cpp imatrix quantization of Salesforce/xLAM-8x7b-r_ |
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Original Model: [Salesforce/xLAM-8x7b-r](https://huggingface.co/Salesforce/xLAM-8x7b-r) |
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Original dtype: `BF16` (`bfloat16`) |
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Quantized by: llama.cpp [b3647](https://github.com/ggerganov/llama.cpp/releases/tag/b3647) |
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IMatrix dataset: [here](https://gist.githubusercontent.com/bartowski1182/eb213dccb3571f863da82e99418f81e8/raw/b2869d80f5c16fd7082594248e80144677736635/calibration_datav3.txt) |
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- [Files](#files) |
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- [IMatrix](#imatrix) |
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- [Common Quants](#common-quants) |
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- [All Quants](#all-quants) |
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- [Downloading using huggingface-cli](#downloading-using-huggingface-cli) |
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- [Inference](#inference) |
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- [Simple chat template](#simple-chat-template) |
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- [Chat template with system prompt](#chat-template-with-system-prompt) |
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- [Llama.cpp](#llama-cpp) |
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- [FAQ](#faq) |
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- [Why is the IMatrix not applied everywhere?](#why-is-the-imatrix-not-applied-everywhere) |
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- [How do I merge a split GGUF?](#how-do-i-merge-a-split-gguf) |
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--- |
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## Files |
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### IMatrix |
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Status: ✅ Available |
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Link: [here](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/imatrix.dat) |
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### Common Quants |
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| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split | |
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| -------- | ---------- | --------- | ------ | ------------ | -------- | |
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| [xLAM-8x7b-r.Q8_0/*](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/tree/main/xLAM-8x7b-r.Q8_0) | Q8_0 | 49.63GB | ✅ Available | ⚪ Static | ✂ Yes |
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| [xLAM-8x7b-r.Q6_K.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q6_K.gguf) | Q6_K | 38.38GB | ✅ Available | ⚪ Static | 📦 No |
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| [xLAM-8x7b-r.Q4_K.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q4_K.gguf) | Q4_K | 28.45GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.Q3_K.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q3_K.gguf) | Q3_K | 22.55GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.Q2_K.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q2_K.gguf) | Q2_K | 17.31GB | ✅ Available | 🟢 IMatrix | 📦 No |
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### All Quants |
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| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split | |
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| -------- | ---------- | --------- | ------ | ------------ | -------- | |
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| [xLAM-8x7b-r.BF16/*](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/tree/main/xLAM-8x7b-r.BF16) | BF16 | 93.41GB | ✅ Available | ⚪ Static | ✂ Yes |
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| [xLAM-8x7b-r.FP16/*](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/tree/main/xLAM-8x7b-r.FP16) | F16 | 93.41GB | ✅ Available | ⚪ Static | ✂ Yes |
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| [xLAM-8x7b-r.Q8_0/*](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/tree/main/xLAM-8x7b-r.Q8_0) | Q8_0 | 49.63GB | ✅ Available | ⚪ Static | ✂ Yes |
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| [xLAM-8x7b-r.Q6_K.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q6_K.gguf) | Q6_K | 38.38GB | ✅ Available | ⚪ Static | 📦 No |
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| [xLAM-8x7b-r.Q5_K.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q5_K.gguf) | Q5_K | 33.23GB | ✅ Available | ⚪ Static | 📦 No |
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| [xLAM-8x7b-r.Q5_K_S.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q5_K_S.gguf) | Q5_K_S | 32.23GB | ✅ Available | ⚪ Static | 📦 No |
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| [xLAM-8x7b-r.Q4_K.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q4_K.gguf) | Q4_K | 28.45GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.Q4_K_S.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q4_K_S.gguf) | Q4_K_S | 26.75GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.IQ4_NL.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.IQ4_NL.gguf) | IQ4_NL | 26.51GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.IQ4_XS.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.IQ4_XS.gguf) | IQ4_XS | 25.08GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.Q3_K.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q3_K.gguf) | Q3_K | 22.55GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.Q3_K_L.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q3_K_L.gguf) | Q3_K_L | 24.17GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.Q3_K_S.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q3_K_S.gguf) | Q3_K_S | 20.43GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.IQ3_M.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.IQ3_M.gguf) | IQ3_M | 21.43GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.IQ3_S.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.IQ3_S.gguf) | IQ3_S | 20.43GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.IQ3_XS.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.IQ3_XS.gguf) | IQ3_XS | 19.35GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| xLAM-8x7b-r.IQ3_XXS | IQ3_XXS | - | ⏳ Processing | 🟢 IMatrix | - |
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| [xLAM-8x7b-r.Q2_K.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q2_K.gguf) | Q2_K | 17.31GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| [xLAM-8x7b-r.Q2_K_S.gguf](https://huggingface.co/legraphista/xLAM-8x7b-r-IMat-GGUF/blob/main/xLAM-8x7b-r.Q2_K_S.gguf) | Q2_K_S | 16.03GB | ✅ Available | 🟢 IMatrix | 📦 No |
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| xLAM-8x7b-r.IQ2_M | IQ2_M | - | ⏳ Processing | 🟢 IMatrix | - |
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| xLAM-8x7b-r.IQ2_S | IQ2_S | - | ⏳ Processing | 🟢 IMatrix | - |
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| xLAM-8x7b-r.IQ2_XS | IQ2_XS | - | ⏳ Processing | 🟢 IMatrix | - |
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| xLAM-8x7b-r.IQ2_XXS | IQ2_XXS | - | ⏳ Processing | 🟢 IMatrix | - |
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| xLAM-8x7b-r.IQ1_M | IQ1_M | - | ⏳ Processing | 🟢 IMatrix | - |
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| xLAM-8x7b-r.IQ1_S | IQ1_S | - | ⏳ Processing | 🟢 IMatrix | - |
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## Downloading using huggingface-cli |
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If you do not have hugginface-cli installed: |
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``` |
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pip install -U "huggingface_hub[cli]" |
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``` |
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Download the specific file you want: |
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``` |
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huggingface-cli download legraphista/xLAM-8x7b-r-IMat-GGUF --include "xLAM-8x7b-r.Q8_0.gguf" --local-dir ./ |
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``` |
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If the model file is big, it has been split into multiple files. In order to download them all to a local folder, run: |
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``` |
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huggingface-cli download legraphista/xLAM-8x7b-r-IMat-GGUF --include "xLAM-8x7b-r.Q8_0/*" --local-dir ./ |
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# see FAQ for merging GGUF's |
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``` |
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--- |
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## Inference |
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### Simple chat template |
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``` |
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<s> [INST] {user_prompt} [/INST] {assistant_response}</s> [INST] {next_user_prompt} [/INST] |
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``` |
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### Chat template with system prompt |
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``` |
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<s> [INST] {system_prompt} |
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{user_prompt} [/INST] {assistant_response}</s> [INST] {next_user_prompt} [/INST] |
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``` |
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### Llama.cpp |
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``` |
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llama.cpp/main -m xLAM-8x7b-r.Q8_0.gguf --color -i -p "prompt here (according to the chat template)" |
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``` |
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--- |
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## FAQ |
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### Why is the IMatrix not applied everywhere? |
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According to [this investigation](https://www.reddit.com/r/LocalLLaMA/comments/1993iro/ggufs_quants_can_punch_above_their_weights_now/), it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results). |
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### How do I merge a split GGUF? |
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1. Make sure you have `gguf-split` available |
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- To get hold of `gguf-split`, navigate to https://github.com/ggerganov/llama.cpp/releases |
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- Download the appropriate zip for your system from the latest release |
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- Unzip the archive and you should be able to find `gguf-split` |
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2. Locate your GGUF chunks folder (ex: `xLAM-8x7b-r.Q8_0`) |
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3. Run `gguf-split --merge xLAM-8x7b-r.Q8_0/xLAM-8x7b-r.Q8_0-00001-of-XXXXX.gguf xLAM-8x7b-r.Q8_0.gguf` |
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- Make sure to point `gguf-split` to the first chunk of the split. |
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--- |
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Got a suggestion? Ping me [@legraphista](https://x.com/legraphista)! |
