GGUF
Mixture of Experts
mixtral
openchat/openchat-3.5-0106
giux78/zefiro-7b-beta-ITA-v0.1
azale-ai/Starstreak-7b-beta
gagan3012/Mistral_arabic_dpo
davidkim205/komt-mistral-7b-v1
OpenBuddy/openbuddy-zephyr-7b-v14.1
manishiitg/open-aditi-hi-v1
VAGOsolutions/SauerkrautLM-7b-v1-mistral
TensorBlock
GGUF
Eval Results
Inference Endpoints
conversational
| license: apache-2.0 | |
| tags: | |
| - moe | |
| - mixtral | |
| - openchat/openchat-3.5-0106 | |
| - giux78/zefiro-7b-beta-ITA-v0.1 | |
| - azale-ai/Starstreak-7b-beta | |
| - gagan3012/Mistral_arabic_dpo | |
| - davidkim205/komt-mistral-7b-v1 | |
| - OpenBuddy/openbuddy-zephyr-7b-v14.1 | |
| - manishiitg/open-aditi-hi-v1 | |
| - VAGOsolutions/SauerkrautLM-7b-v1-mistral | |
| - TensorBlock | |
| - GGUF | |
| base_model: gagan3012/Multilingual-mistral | |
| model-index: | |
| - name: Multilingual-mistral | |
| results: | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: AI2 Reasoning Challenge (25-Shot) | |
| type: ai2_arc | |
| config: ARC-Challenge | |
| split: test | |
| args: | |
| num_few_shot: 25 | |
| metrics: | |
| - type: acc_norm | |
| value: 62.29 | |
| name: normalized accuracy | |
| source: | |
| url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/Multilingual-mistral | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: HellaSwag (10-Shot) | |
| type: hellaswag | |
| split: validation | |
| args: | |
| num_few_shot: 10 | |
| metrics: | |
| - type: acc_norm | |
| value: 81.76 | |
| name: normalized accuracy | |
| source: | |
| url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/Multilingual-mistral | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: MMLU (5-Shot) | |
| type: cais/mmlu | |
| config: all | |
| split: test | |
| args: | |
| num_few_shot: 5 | |
| metrics: | |
| - type: acc | |
| value: 61.38 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/Multilingual-mistral | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: TruthfulQA (0-shot) | |
| type: truthful_qa | |
| config: multiple_choice | |
| split: validation | |
| args: | |
| num_few_shot: 0 | |
| metrics: | |
| - type: mc2 | |
| value: 55.53 | |
| source: | |
| url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/Multilingual-mistral | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: Winogrande (5-shot) | |
| type: winogrande | |
| config: winogrande_xl | |
| split: validation | |
| args: | |
| num_few_shot: 5 | |
| metrics: | |
| - type: acc | |
| value: 75.53 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/Multilingual-mistral | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: GSM8k (5-shot) | |
| type: gsm8k | |
| config: main | |
| split: test | |
| args: | |
| num_few_shot: 5 | |
| metrics: | |
| - type: acc | |
| value: 40.26 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/Multilingual-mistral | |
| 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> | |
| ## gagan3012/Multilingual-mistral - GGUF | |
| This repo contains GGUF format model files for [gagan3012/Multilingual-mistral](https://huggingface.co./gagan3012/Multilingual-mistral). | |
| 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). | |
| <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 | |
| ``` | |
| <s>[INST] {prompt} [/INST] | |
| ``` | |
| ## Model file specification | |
| | Filename | Quant type | File Size | Description | | |
| | -------- | ---------- | --------- | ----------- | | |
| | [Multilingual-mistral-Q2_K.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q2_K.gguf) | Q2_K | 17.311 GB | smallest, significant quality loss - not recommended for most purposes | | |
| | [Multilingual-mistral-Q3_K_S.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q3_K_S.gguf) | Q3_K_S | 20.433 GB | very small, high quality loss | | |
| | [Multilingual-mistral-Q3_K_M.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q3_K_M.gguf) | Q3_K_M | 22.546 GB | very small, high quality loss | | |
| | [Multilingual-mistral-Q3_K_L.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q3_K_L.gguf) | Q3_K_L | 24.170 GB | small, substantial quality loss | | |
| | [Multilingual-mistral-Q4_0.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q4_0.gguf) | Q4_0 | 26.444 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | |
| | [Multilingual-mistral-Q4_K_S.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q4_K_S.gguf) | Q4_K_S | 26.746 GB | small, greater quality loss | | |
| | [Multilingual-mistral-Q4_K_M.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q4_K_M.gguf) | Q4_K_M | 28.448 GB | medium, balanced quality - recommended | | |
| | [Multilingual-mistral-Q5_0.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q5_0.gguf) | Q5_0 | 32.231 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | |
| | [Multilingual-mistral-Q5_K_S.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q5_K_S.gguf) | Q5_K_S | 32.231 GB | large, low quality loss - recommended | | |
| | [Multilingual-mistral-Q5_K_M.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q5_K_M.gguf) | Q5_K_M | 33.230 GB | large, very low quality loss - recommended | | |
| | [Multilingual-mistral-Q6_K.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q6_K.gguf) | Q6_K | 38.381 GB | very large, extremely low quality loss | | |
| | [Multilingual-mistral-Q8_0.gguf](https://huggingface.co./tensorblock/Multilingual-mistral-GGUF/blob/main/Multilingual-mistral-Q8_0.gguf) | Q8_0 | 49.626 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/Multilingual-mistral-GGUF --include "Multilingual-mistral-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/Multilingual-mistral-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' | |
| ``` | |