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  *.zip filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
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+ base-eval-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ language:
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+ - en
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+ - de
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+ - fr
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+ - it
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+ - pt
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+ - hi
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+ - es
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+ - th
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+ license: llama3.1
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+ base_model: deval-core/base-eval
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+ pipeline_tag: text-generation
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+ tags:
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+ - facebook
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+ - meta
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+ - pytorch
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+ - llama
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+ - llama-3
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+ - TensorBlock
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+ - GGUF
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+ extra_gated_prompt: "### LLAMA 3.1 COMMUNITY LICENSE AGREEMENT\nLlama 3.1 Version\
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+ \ Release Date: July 23, 2024\n\"Agreement\" means the terms and conditions for\
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+ \ if you are in breach of any term or condition of this Agreement. Upon termination\
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+ \ 3, 4 and 7 shall survive the termination of this Agreement.\n7. Governing Law\
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+ \ and Jurisdiction. This Agreement will be governed and construed under the laws\
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+ \ of any dispute arising out of this Agreement.\n### Llama 3.1 Acceptable Use Policy\n\
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+ Meta is committed to promoting safe and fair use of its tools and features, including\
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+ #### Prohibited Uses\nWe want everyone to use Llama 3.1 safely and responsibly.\
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+ \ State\n 2. Guns and illegal weapons (including weapon development)\n 3.\
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+ \ Illegal drugs and regulated/controlled substances\n 4. Operation of critical\
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+ \ infrastructure, transportation technologies, or heavy machinery\n 5. Self-harm\
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+ \ or harm to others, including suicide, cutting, and eating disorders\n 6. Any\
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+ \ content intended to incite or promote violence, abuse, or any infliction of bodily\
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+ \ harm to an individual\n3. Intentionally deceive or mislead others, including use\
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+ \ of Llama 3.1 related to the following:\n 1. Generating, promoting, or furthering\
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+ \ fraud or the creation or promotion of disinformation\n 2. Generating, promoting,\
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+ \ or furthering defamatory content, including the creation of defamatory statements,\
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+ \ images, or other content\n 3. Generating, promoting, or further distributing\
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+ \ spam\n 4. Impersonating another individual without consent, authorization,\
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+ \ or legal right\n 5. Representing that the use of Llama 3.1 or outputs are human-generated\n\
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+ \ 6. Generating or facilitating false online engagement, including fake reviews\
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+ \ and other means of fake online engagement\n4. Fail to appropriately disclose to\
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+ \ end users any known dangers of your AI system\nPlease report any violation of\
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+ \ this Policy, software “bug,” or other problems that could lead to a violation\
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+ \ of this Policy through one of the following means:\n * Reporting issues with\
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+ \ the model: [https://github.com/meta-llama/llama-models/issues](https://github.com/meta-llama/llama-models/issues)\n\
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+ \ * Reporting risky content generated by the model:\n developers.facebook.com/llama_output_feedback\n\
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+ \ * Reporting bugs and security concerns: facebook.com/whitehat/info\n * Reporting\
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+ \ violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3: [email protected]"
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+ extra_gated_fields:
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+ First Name: text
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+ Last Name: text
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+ Date of birth: date_picker
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+ Country: country
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+ Affiliation: text
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+ Job title:
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+ type: select
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+ options:
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+ - Student
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+ - Research Graduate
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+ - AI researcher
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+ - AI developer/engineer
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+ - Reporter
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+ - Other
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+ geo: ip_location
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+ ? By clicking Submit below I accept the terms of the license and acknowledge that
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+ the information I provide will be collected stored processed and shared in accordance
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+ with the Meta Privacy Policy
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+ : checkbox
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+ extra_gated_description: The information you provide will be collected, stored, processed
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+ and shared in accordance with the [Meta Privacy Policy](https://www.facebook.com/privacy/policy/).
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+ extra_gated_button_content: Submit
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+ ---
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+
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+ <div style="width: auto; margin-left: auto; margin-right: auto">
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+ <img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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+ </div>
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+ <div style="display: flex; justify-content: space-between; width: 100%;">
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+ <div style="display: flex; flex-direction: column; align-items: flex-start;">
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+ <p style="margin-top: 0.5em; margin-bottom: 0em;">
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+ Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
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+ </p>
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+ </div>
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+ </div>
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+
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+ ## deval-core/base-eval - GGUF
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+
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+ This repo contains GGUF format model files for [deval-core/base-eval](https://huggingface.co/deval-core/base-eval).
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+
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+ The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
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+
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+ <div style="text-align: left; margin: 20px 0;">
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+ <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
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+ Run them on the TensorBlock client using your local machine ↗
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+ </a>
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+ </div>
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+
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+ ## Prompt template
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+
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+ ```
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+ <|begin_of_text|><|start_header_id|>system<|end_header_id|>
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+
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+ Cutting Knowledge Date: December 2023
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+ Today Date: 26 Jul 2024
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+
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+ {system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
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+
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+ {prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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+ ```
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+
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+ ## Model file specification
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+
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+ | Filename | Quant type | File Size | Description |
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+ | -------- | ---------- | --------- | ----------- |
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+ | [base-eval-Q2_K.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q2_K.gguf) | Q2_K | 3.179 GB | smallest, significant quality loss - not recommended for most purposes |
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+ | [base-eval-Q3_K_S.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q3_K_S.gguf) | Q3_K_S | 3.665 GB | very small, high quality loss |
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+ | [base-eval-Q3_K_M.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q3_K_M.gguf) | Q3_K_M | 4.019 GB | very small, high quality loss |
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+ | [base-eval-Q3_K_L.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q3_K_L.gguf) | Q3_K_L | 4.322 GB | small, substantial quality loss |
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+ | [base-eval-Q4_0.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q4_0.gguf) | Q4_0 | 4.661 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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+ | [base-eval-Q4_K_S.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q4_K_S.gguf) | Q4_K_S | 4.693 GB | small, greater quality loss |
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+ | [base-eval-Q4_K_M.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q4_K_M.gguf) | Q4_K_M | 4.921 GB | medium, balanced quality - recommended |
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+ | [base-eval-Q5_0.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q5_0.gguf) | Q5_0 | 5.599 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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+ | [base-eval-Q5_K_S.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q5_K_S.gguf) | Q5_K_S | 5.599 GB | large, low quality loss - recommended |
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+ | [base-eval-Q5_K_M.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q5_K_M.gguf) | Q5_K_M | 5.733 GB | large, very low quality loss - recommended |
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+ | [base-eval-Q6_K.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q6_K.gguf) | Q6_K | 6.596 GB | very large, extremely low quality loss |
245
+ | [base-eval-Q8_0.gguf](https://huggingface.co/tensorblock/base-eval-GGUF/blob/main/base-eval-Q8_0.gguf) | Q8_0 | 8.541 GB | very large, extremely low quality loss - not recommended |
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+
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+
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+ ## Downloading instruction
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+
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+ ### Command line
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+
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+ Firstly, install Huggingface Client
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+
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+ ```shell
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+ pip install -U "huggingface_hub[cli]"
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+ ```
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+
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+ Then, downoad the individual model file the a local directory
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+
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+ ```shell
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+ huggingface-cli download tensorblock/base-eval-GGUF --include "base-eval-Q2_K.gguf" --local-dir MY_LOCAL_DIR
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+ ```
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+
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+ If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
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+
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+ ```shell
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+ huggingface-cli download tensorblock/base-eval-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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+ ```
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