Text Generation
GGUF
English
shining-valiant
shining-valiant-2
valiant
valiant-labs
llama
llama-3.1
llama-3.1-instruct
llama-3.1-instruct-8b
llama-3
llama-3-instruct
llama-3-instruct-8b
8b
science
physics
biology
chemistry
compsci
computer-science
engineering
technical
conversational
chat
instruct
TensorBlock
GGUF
Eval Results
Inference Endpoints
| language: | |
| - en | |
| pipeline_tag: text-generation | |
| tags: | |
| - shining-valiant | |
| - shining-valiant-2 | |
| - valiant | |
| - valiant-labs | |
| - llama | |
| - llama-3.1 | |
| - llama-3.1-instruct | |
| - llama-3.1-instruct-8b | |
| - llama-3 | |
| - llama-3-instruct | |
| - llama-3-instruct-8b | |
| - 8b | |
| - science | |
| - physics | |
| - biology | |
| - chemistry | |
| - compsci | |
| - computer-science | |
| - engineering | |
| - technical | |
| - conversational | |
| - chat | |
| - instruct | |
| - TensorBlock | |
| - GGUF | |
| base_model: ValiantLabs/Llama3.1-8B-ShiningValiant2 | |
| datasets: | |
| - sequelbox/Celestia | |
| - sequelbox/Spurline | |
| - sequelbox/Supernova | |
| model_type: llama | |
| license: llama3.1 | |
| model-index: | |
| - name: Llama3.1-8B-ShiningValiant2 | |
| results: | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: Winogrande (5-Shot) | |
| type: Winogrande | |
| args: | |
| num_few_shot: 5 | |
| metrics: | |
| - type: acc | |
| value: 75.85 | |
| name: acc | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: MMLU College Biology (5-Shot) | |
| type: MMLU | |
| args: | |
| num_few_shot: 5 | |
| metrics: | |
| - type: acc | |
| value: 68.75 | |
| name: acc | |
| - type: acc | |
| value: 73.23 | |
| name: acc | |
| - type: acc | |
| value: 46.0 | |
| name: acc | |
| - type: acc | |
| value: 44.33 | |
| name: acc | |
| - type: acc | |
| value: 53.19 | |
| name: acc | |
| - type: acc | |
| value: 37.25 | |
| name: acc | |
| - type: acc | |
| value: 42.38 | |
| name: acc | |
| - type: acc | |
| value: 56.0 | |
| name: acc | |
| - type: acc | |
| value: 63.0 | |
| name: acc | |
| - type: acc | |
| value: 63.16 | |
| name: acc | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: IFEval (0-Shot) | |
| type: HuggingFaceH4/ifeval | |
| args: | |
| num_few_shot: 0 | |
| metrics: | |
| - type: inst_level_strict_acc and prompt_level_strict_acc | |
| value: 65.24 | |
| name: strict accuracy | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2 | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: BBH (3-Shot) | |
| type: BBH | |
| args: | |
| num_few_shot: 3 | |
| metrics: | |
| - type: acc_norm | |
| value: 26.35 | |
| name: normalized accuracy | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2 | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: MATH Lvl 5 (4-Shot) | |
| type: hendrycks/competition_math | |
| args: | |
| num_few_shot: 4 | |
| metrics: | |
| - type: exact_match | |
| value: 11.63 | |
| name: exact match | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2 | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: GPQA (0-shot) | |
| type: Idavidrein/gpqa | |
| args: | |
| num_few_shot: 0 | |
| metrics: | |
| - type: acc_norm | |
| value: 8.95 | |
| name: acc_norm | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2 | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: MuSR (0-shot) | |
| type: TAUR-Lab/MuSR | |
| args: | |
| num_few_shot: 0 | |
| metrics: | |
| - type: acc_norm | |
| value: 7.19 | |
| name: acc_norm | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2 | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: MMLU-PRO (5-shot) | |
| type: TIGER-Lab/MMLU-Pro | |
| config: main | |
| split: test | |
| args: | |
| num_few_shot: 5 | |
| metrics: | |
| - type: acc | |
| value: 26.38 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.1-8B-ShiningValiant2 | |
| name: Open LLM Leaderboard | |
| <div style="width: auto; margin-left: auto; margin-right: auto"> | |
| <img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;"> | |
| </div> | |
| <div style="display: flex; justify-content: space-between; width: 100%;"> | |
| <div style="display: flex; flex-direction: column; align-items: flex-start;"> | |
| <p style="margin-top: 0.5em; margin-bottom: 0em;"> | |
| 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> | |
| </p> | |
| </div> | |
| </div> | |
| ## ValiantLabs/Llama3.1-8B-ShiningValiant2 - GGUF | |
| This repo contains GGUF format model files for [ValiantLabs/Llama3.1-8B-ShiningValiant2](https://huggingface.co/ValiantLabs/Llama3.1-8B-ShiningValiant2). | |
| 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). | |
| <div style="text-align: left; margin: 20px 0;"> | |
| <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;"> | |
| Run them on the TensorBlock client using your local machine ↗ | |
| </a> | |
| </div> | |
| ## 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 | | |
| | -------- | ---------- | --------- | ----------- | | |
| | [Llama3.1-8B-ShiningValiant2-Q2_K.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q2_K.gguf) | Q2_K | 2.961 GB | smallest, significant quality loss - not recommended for most purposes | | |
| | [Llama3.1-8B-ShiningValiant2-Q3_K_S.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q3_K_S.gguf) | Q3_K_S | 3.413 GB | very small, high quality loss | | |
| | [Llama3.1-8B-ShiningValiant2-Q3_K_M.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q3_K_M.gguf) | Q3_K_M | 3.743 GB | very small, high quality loss | | |
| | [Llama3.1-8B-ShiningValiant2-Q3_K_L.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q3_K_L.gguf) | Q3_K_L | 4.025 GB | small, substantial quality loss | | |
| | [Llama3.1-8B-ShiningValiant2-Q4_0.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q4_0.gguf) | Q4_0 | 4.341 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | |
| | [Llama3.1-8B-ShiningValiant2-Q4_K_S.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q4_K_S.gguf) | Q4_K_S | 4.370 GB | small, greater quality loss | | |
| | [Llama3.1-8B-ShiningValiant2-Q4_K_M.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q4_K_M.gguf) | Q4_K_M | 4.583 GB | medium, balanced quality - recommended | | |
| | [Llama3.1-8B-ShiningValiant2-Q5_0.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q5_0.gguf) | Q5_0 | 5.215 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | |
| | [Llama3.1-8B-ShiningValiant2-Q5_K_S.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q5_K_S.gguf) | Q5_K_S | 5.215 GB | large, low quality loss - recommended | | |
| | [Llama3.1-8B-ShiningValiant2-Q5_K_M.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q5_K_M.gguf) | Q5_K_M | 5.339 GB | large, very low quality loss - recommended | | |
| | [Llama3.1-8B-ShiningValiant2-Q6_K.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q6_K.gguf) | Q6_K | 6.143 GB | very large, extremely low quality loss | | |
| | [Llama3.1-8B-ShiningValiant2-Q8_0.gguf](https://huggingface.co/tensorblock/Llama3.1-8B-ShiningValiant2-GGUF/blob/main/Llama3.1-8B-ShiningValiant2-Q8_0.gguf) | Q8_0 | 7.954 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/Llama3.1-8B-ShiningValiant2-GGUF --include "Llama3.1-8B-ShiningValiant2-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/Llama3.1-8B-ShiningValiant2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' | |
| ``` | |