Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
- README.md +89 -0
- falcon-7b-instruct-sharded-Q2_K.gguf +3 -0
- falcon-7b-instruct-sharded-Q3_K_L.gguf +3 -0
- falcon-7b-instruct-sharded-Q3_K_M.gguf +3 -0
- falcon-7b-instruct-sharded-Q3_K_S.gguf +3 -0
- falcon-7b-instruct-sharded-Q4_0.gguf +3 -0
- falcon-7b-instruct-sharded-Q4_K_M.gguf +3 -0
- falcon-7b-instruct-sharded-Q4_K_S.gguf +3 -0
- falcon-7b-instruct-sharded-Q5_0.gguf +3 -0
- falcon-7b-instruct-sharded-Q5_K_M.gguf +3 -0
- falcon-7b-instruct-sharded-Q5_K_S.gguf +3 -0
- falcon-7b-instruct-sharded-Q6_K.gguf +3 -0
- falcon-7b-instruct-sharded-Q8_0.gguf +3 -0
.gitattributes
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falcon-7b-instruct-sharded-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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datasets:
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- tiiuae/falcon-refinedweb
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language:
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- en
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inference: true
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widget:
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- text: Hey Falcon! Any recommendations for my holidays in Abu Dhabi?
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example_title: Abu Dhabi Trip
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+
- text: What's the Everett interpretation of quantum mechanics?
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example_title: 'Q/A: Quantum & Answers'
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- text: Give me a list of the top 10 dive sites you would recommend around the world.
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example_title: Diving Top 10
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- text: Can you tell me more about deep-water soloing?
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example_title: Extreme sports
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- text: Can you write a short tweet about the Apache 2.0 release of our latest AI
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model, Falcon LLM?
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example_title: Twitter Helper
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- text: What are the responsabilities of a Chief Llama Officer?
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example_title: Trendy Jobs
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license: apache-2.0
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base_model: vilsonrodrigues/falcon-7b-instruct-sharded
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tags:
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- TensorBlock
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- GGUF
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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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## vilsonrodrigues/falcon-7b-instruct-sharded - GGUF
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This repo contains GGUF format model files for [vilsonrodrigues/falcon-7b-instruct-sharded](https://huggingface.co/vilsonrodrigues/falcon-7b-instruct-sharded).
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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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## Prompt template
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```
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```
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## Model file specification
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [falcon-7b-instruct-sharded-Q2_K.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q2_K.gguf) | Q2_K | 3.440 GB | smallest, significant quality loss - not recommended for most purposes |
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| [falcon-7b-instruct-sharded-Q3_K_S.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q3_K_S.gguf) | Q3_K_S | 3.440 GB | very small, high quality loss |
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| [falcon-7b-instruct-sharded-Q3_K_M.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q3_K_M.gguf) | Q3_K_M | 3.702 GB | very small, high quality loss |
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| [falcon-7b-instruct-sharded-Q3_K_L.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q3_K_L.gguf) | Q3_K_L | 3.923 GB | small, substantial quality loss |
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| [falcon-7b-instruct-sharded-Q4_0.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q4_0.gguf) | Q4_0 | 3.767 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| [falcon-7b-instruct-sharded-Q4_K_S.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q4_K_S.gguf) | Q4_K_S | 4.230 GB | small, greater quality loss |
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| [falcon-7b-instruct-sharded-Q4_K_M.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q4_K_M.gguf) | Q4_K_M | 4.444 GB | medium, balanced quality - recommended |
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| [falcon-7b-instruct-sharded-Q5_0.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q5_0.gguf) | Q5_0 | 4.538 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| [falcon-7b-instruct-sharded-Q5_K_S.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q5_K_S.gguf) | Q5_K_S | 4.770 GB | large, low quality loss - recommended |
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| [falcon-7b-instruct-sharded-Q5_K_M.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q5_K_M.gguf) | Q5_K_M | 5.131 GB | large, very low quality loss - recommended |
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| [falcon-7b-instruct-sharded-Q6_K.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q6_K.gguf) | Q6_K | 6.256 GB | very large, extremely low quality loss |
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| [falcon-7b-instruct-sharded-Q8_0.gguf](https://huggingface.co/tensorblock/falcon-7b-instruct-sharded-GGUF/tree/main/falcon-7b-instruct-sharded-Q8_0.gguf) | Q8_0 | 6.852 GB | very large, extremely low quality loss - not recommended |
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## Downloading instruction
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|
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### Command line
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72 |
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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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```shell
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huggingface-cli download tensorblock/falcon-7b-instruct-sharded-GGUF --include "falcon-7b-instruct-sharded-Q2_K.gguf" --local-dir MY_LOCAL_DIR
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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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```shell
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huggingface-cli download tensorblock/falcon-7b-instruct-sharded-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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```
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falcon-7b-instruct-sharded-Q2_K.gguf
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