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- Llama-3.2-SUN-2.5B-chat-Q2_K.gguf +3 -0
- Llama-3.2-SUN-2.5B-chat-Q3_K_L.gguf +3 -0
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- Llama-3.2-SUN-2.5B-chat-Q8_0.gguf +3 -0
- README.md +190 -0
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README.md
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| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- en
|
| 4 |
+
license: llama3.2
|
| 5 |
+
library_name: transformers
|
| 6 |
+
base_model: meditsolutions/Llama-3.2-SUN-2.5B-chat
|
| 7 |
+
datasets:
|
| 8 |
+
- argilla/OpenHermesPreferences
|
| 9 |
+
- argilla/magpie-ultra-v0.1
|
| 10 |
+
- argilla/Capybara-Preferences-Filtered
|
| 11 |
+
- mlabonne/open-perfectblend
|
| 12 |
+
- HuggingFaceTB/everyday-conversations-llama3.1-2k
|
| 13 |
+
- WizardLMTeam/WizardLM_evol_instruct_V2_196k
|
| 14 |
+
- ProlificAI/social-reasoning-rlhf
|
| 15 |
+
pipeline_tag: text-generation
|
| 16 |
+
tags:
|
| 17 |
+
- TensorBlock
|
| 18 |
+
- GGUF
|
| 19 |
+
model-index:
|
| 20 |
+
- name: Llama-3.2-SUN-2.5B-chat
|
| 21 |
+
results:
|
| 22 |
+
- task:
|
| 23 |
+
type: text-generation
|
| 24 |
+
name: Text Generation
|
| 25 |
+
dataset:
|
| 26 |
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name: IFEval (0-Shot)
|
| 27 |
+
type: HuggingFaceH4/ifeval
|
| 28 |
+
args:
|
| 29 |
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num_few_shot: 0
|
| 30 |
+
metrics:
|
| 31 |
+
- type: inst_level_strict_acc and prompt_level_strict_acc
|
| 32 |
+
value: 56.04
|
| 33 |
+
name: strict accuracy
|
| 34 |
+
source:
|
| 35 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-2.5B-chat
|
| 36 |
+
name: Open LLM Leaderboard
|
| 37 |
+
- task:
|
| 38 |
+
type: text-generation
|
| 39 |
+
name: Text Generation
|
| 40 |
+
dataset:
|
| 41 |
+
name: BBH (3-Shot)
|
| 42 |
+
type: BBH
|
| 43 |
+
args:
|
| 44 |
+
num_few_shot: 3
|
| 45 |
+
metrics:
|
| 46 |
+
- type: acc_norm
|
| 47 |
+
value: 9.41
|
| 48 |
+
name: normalized accuracy
|
| 49 |
+
source:
|
| 50 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-2.5B-chat
|
| 51 |
+
name: Open LLM Leaderboard
|
| 52 |
+
- task:
|
| 53 |
+
type: text-generation
|
| 54 |
+
name: Text Generation
|
| 55 |
+
dataset:
|
| 56 |
+
name: MATH Lvl 5 (4-Shot)
|
| 57 |
+
type: hendrycks/competition_math
|
| 58 |
+
args:
|
| 59 |
+
num_few_shot: 4
|
| 60 |
+
metrics:
|
| 61 |
+
- type: exact_match
|
| 62 |
+
value: 5.06
|
| 63 |
+
name: exact match
|
| 64 |
+
source:
|
| 65 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-2.5B-chat
|
| 66 |
+
name: Open LLM Leaderboard
|
| 67 |
+
- task:
|
| 68 |
+
type: text-generation
|
| 69 |
+
name: Text Generation
|
| 70 |
+
dataset:
|
| 71 |
+
name: GPQA (0-shot)
|
| 72 |
+
type: Idavidrein/gpqa
|
| 73 |
+
args:
|
| 74 |
+
num_few_shot: 0
|
| 75 |
+
metrics:
|
| 76 |
+
- type: acc_norm
|
| 77 |
+
value: 1.23
|
| 78 |
+
name: acc_norm
|
| 79 |
+
source:
|
| 80 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-2.5B-chat
|
| 81 |
+
name: Open LLM Leaderboard
|
| 82 |
+
- task:
|
| 83 |
+
type: text-generation
|
| 84 |
+
name: Text Generation
|
| 85 |
+
dataset:
|
| 86 |
+
name: MuSR (0-shot)
|
| 87 |
+
type: TAUR-Lab/MuSR
|
| 88 |
+
args:
|
| 89 |
+
num_few_shot: 0
|
| 90 |
+
metrics:
|
| 91 |
+
- type: acc_norm
|
| 92 |
+
value: 1.11
|
| 93 |
+
name: acc_norm
|
| 94 |
+
source:
|
| 95 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-2.5B-chat
|
| 96 |
+
name: Open LLM Leaderboard
|
| 97 |
+
- task:
|
| 98 |
+
type: text-generation
|
| 99 |
+
name: Text Generation
|
| 100 |
+
dataset:
|
| 101 |
+
name: MMLU-PRO (5-shot)
|
| 102 |
+
type: TIGER-Lab/MMLU-Pro
|
| 103 |
+
config: main
|
| 104 |
+
split: test
|
| 105 |
+
args:
|
| 106 |
+
num_few_shot: 5
|
| 107 |
+
metrics:
|
| 108 |
+
- type: acc
|
| 109 |
+
value: 9.04
|
| 110 |
+
name: accuracy
|
| 111 |
+
source:
|
| 112 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=meditsolutions/Llama-3.2-SUN-2.5B-chat
|
| 113 |
+
name: Open LLM Leaderboard
|
| 114 |
+
---
|
| 115 |
+
|
| 116 |
+
<div style="width: auto; margin-left: auto; margin-right: auto">
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| 117 |
+
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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| 118 |
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</div>
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| 119 |
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<div style="display: flex; justify-content: space-between; width: 100%;">
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| 120 |
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<div style="display: flex; flex-direction: column; align-items: flex-start;">
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| 121 |
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<p style="margin-top: 0.5em; margin-bottom: 0em;">
|
| 122 |
+
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>
|
| 123 |
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</p>
|
| 124 |
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</div>
|
| 125 |
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</div>
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| 126 |
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| 127 |
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## meditsolutions/Llama-3.2-SUN-2.5B-chat - GGUF
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This repo contains GGUF format model files for [meditsolutions/Llama-3.2-SUN-2.5B-chat](https://huggingface.co/meditsolutions/Llama-3.2-SUN-2.5B-chat).
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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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<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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## Prompt template
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```
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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Cutting Knowledge Date: December 2023
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Today Date: 25 Nov 2024
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{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
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{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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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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| [Llama-3.2-SUN-2.5B-chat-Q2_K.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q2_K.gguf) | Q2_K | 1.025 GB | smallest, significant quality loss - not recommended for most purposes |
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| [Llama-3.2-SUN-2.5B-chat-Q3_K_S.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q3_K_S.gguf) | Q3_K_S | 1.173 GB | very small, high quality loss |
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| [Llama-3.2-SUN-2.5B-chat-Q3_K_M.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q3_K_M.gguf) | Q3_K_M | 1.271 GB | very small, high quality loss |
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| [Llama-3.2-SUN-2.5B-chat-Q3_K_L.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q3_K_L.gguf) | Q3_K_L | 1.355 GB | small, substantial quality loss |
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| [Llama-3.2-SUN-2.5B-chat-Q4_0.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q4_0.gguf) | Q4_0 | 1.466 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| [Llama-3.2-SUN-2.5B-chat-Q4_K_S.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q4_K_S.gguf) | Q4_K_S | 1.475 GB | small, greater quality loss |
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| [Llama-3.2-SUN-2.5B-chat-Q4_K_M.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q4_K_M.gguf) | Q4_K_M | 1.540 GB | medium, balanced quality - recommended |
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| [Llama-3.2-SUN-2.5B-chat-Q5_0.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q5_0.gguf) | Q5_0 | 1.742 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| [Llama-3.2-SUN-2.5B-chat-Q5_K_S.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q5_K_S.gguf) | Q5_K_S | 1.742 GB | large, low quality loss - recommended |
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| [Llama-3.2-SUN-2.5B-chat-Q5_K_M.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q5_K_M.gguf) | Q5_K_M | 1.780 GB | large, very low quality loss - recommended |
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| [Llama-3.2-SUN-2.5B-chat-Q6_K.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q6_K.gguf) | Q6_K | 2.036 GB | very large, extremely low quality loss |
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| [Llama-3.2-SUN-2.5B-chat-Q8_0.gguf](https://huggingface.co/tensorblock/Llama-3.2-SUN-2.5B-chat-GGUF/blob/main/Llama-3.2-SUN-2.5B-chat-Q8_0.gguf) | Q8_0 | 2.634 GB | very large, extremely low quality loss - not recommended |
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## Downloading instruction
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### Command line
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Firstly, install Huggingface Client
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```shell
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pip install -U "huggingface_hub[cli]"
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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/Llama-3.2-SUN-2.5B-chat-GGUF --include "Llama-3.2-SUN-2.5B-chat-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/Llama-3.2-SUN-2.5B-chat-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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```
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