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## meta-llama/Llama-3.3-70B-Instruct - GGUF This repo contains GGUF format model files for [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct). The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
Run them on the TensorBlock client using your local machine ↗
## Prompt template ``` <|begin_of_text|><|start_header_id|>system<|end_header_id|> Cutting Knowledge Date: December 2023 Today Date: 26 Jul 2024 {system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|> {prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|> ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [Llama-3.3-70B-Instruct-Q2_K.gguf](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q2_K.gguf) | Q2_K | 26.375 GB | smallest, significant quality loss - not recommended for most purposes | | [Llama-3.3-70B-Instruct-Q3_K_S.gguf](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q3_K_S.gguf) | Q3_K_S | 30.912 GB | very small, high quality loss | | [Llama-3.3-70B-Instruct-Q3_K_M.gguf](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q3_K_M.gguf) | Q3_K_M | 34.267 GB | very small, high quality loss | | [Llama-3.3-70B-Instruct-Q3_K_L.gguf](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q3_K_L.gguf) | Q3_K_L | 37.141 GB | small, substantial quality loss | | [Llama-3.3-70B-Instruct-Q4_0.gguf](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q4_0.gguf) | Q4_0 | 39.970 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [Llama-3.3-70B-Instruct-Q4_K_S.gguf](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q4_K_S.gguf) | Q4_K_S | 40.347 GB | small, greater quality loss | | [Llama-3.3-70B-Instruct-Q4_K_M.gguf](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q4_K_M.gguf) | Q4_K_M | 42.520 GB | medium, balanced quality - recommended | | [Llama-3.3-70B-Instruct-Q5_0.gguf](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q5_0.gguf) | Q5_0 | 48.657 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [Llama-3.3-70B-Instruct-Q5_K_S.gguf](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q5_K_S.gguf) | Q5_K_S | 48.657 GB | large, low quality loss - recommended | | [Llama-3.3-70B-Instruct-Q5_K_M.gguf](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q5_K_M.gguf) | Q5_K_M | 49.950 GB | large, very low quality loss - recommended | | [Llama-3.3-70B-Instruct-Q8_0](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q8_0) | Q6_K | 74.975 GB | very large, extremely low quality loss | | [Llama-3.3-70B-Instruct-Q6_K](https://huggingface.co/tensorblock/Llama-3.3-70B-Instruct-GGUF/blob/main/Llama-3.3-70B-Instruct-Q6_K) | Q8_0 | 57.888 GB | very large, extremely low quality loss - not recommended | ## Downloading instruction ### Command line Firstly, install Huggingface Client ```shell pip install -U "huggingface_hub[cli]" ``` Then, downoad the individual model file the a local directory ```shell huggingface-cli download tensorblock/Llama-3.3-70B-Instruct-GGUF --include "Llama-3.3-70B-Instruct-Q2_K.gguf" --local-dir MY_LOCAL_DIR ``` If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: ```shell huggingface-cli download tensorblock/Llama-3.3-70B-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```