--- license: apache-2.0 language: - tr base_model: Orbina/Orbita-v0.1 tags: - TensorBlock - GGUF model-index: - name: Orbita-v0.1 results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge TR type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc value: 41.97 name: accuracy - task: type: text-generation name: Text Generation dataset: name: HellaSwag TR type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc value: 48 name: accuracy - task: type: text-generation name: Text Generation dataset: name: MMLU TR type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 49.51 name: accuracy - task: type: text-generation name: Text Generation dataset: name: TruthfulQA TR type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: acc value: 50.78 name: accuracy - task: type: text-generation name: Text Generation dataset: name: Winogrande TR type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 56.16 name: accuracy - task: type: text-generation name: Text Generation dataset: name: GSM8k TR type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 50.41 name: accuracy ---
TensorBlock

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

## Orbina/Orbita-v0.1 - GGUF This repo contains GGUF format model files for [Orbina/Orbita-v0.1](https://huggingface.co/Orbina/Orbita-v0.1). 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). ## Prompt template ``` <|im_start|>system {system_prompt}<|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant ``` ## Model file specification | Filename | Quant type | File Size | Description | | -------- | ---------- | --------- | ----------- | | [Orbita-v0.1-Q2_K.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q2_K.gguf) | Q2_K | 5.506 GB | smallest, significant quality loss - not recommended for most purposes | | [Orbita-v0.1-Q3_K_S.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q3_K_S.gguf) | Q3_K_S | 6.309 GB | very small, high quality loss | | [Orbita-v0.1-Q3_K_M.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q3_K_M.gguf) | Q3_K_M | 6.909 GB | very small, high quality loss | | [Orbita-v0.1-Q3_K_L.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q3_K_L.gguf) | Q3_K_L | 7.302 GB | small, substantial quality loss | | [Orbita-v0.1-Q4_0.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q4_0.gguf) | Q4_0 | 7.618 GB | legacy; small, very high quality loss - prefer using Q3_K_M | | [Orbita-v0.1-Q4_K_S.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q4_K_S.gguf) | Q4_K_S | 7.977 GB | small, greater quality loss | | [Orbita-v0.1-Q4_K_M.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q4_K_M.gguf) | Q4_K_M | 8.560 GB | medium, balanced quality - recommended | | [Orbita-v0.1-Q5_0.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q5_0.gguf) | Q5_0 | 9.176 GB | legacy; medium, balanced quality - prefer using Q4_K_M | | [Orbita-v0.1-Q5_K_S.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q5_K_S.gguf) | Q5_K_S | 9.339 GB | large, low quality loss - recommended | | [Orbita-v0.1-Q5_K_M.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q5_K_M.gguf) | Q5_K_M | 9.812 GB | large, very low quality loss - recommended | | [Orbita-v0.1-Q6_K.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q6_K.gguf) | Q6_K | 11.465 GB | very large, extremely low quality loss | | [Orbita-v0.1-Q8_0.gguf](https://huggingface.co/tensorblock/Orbita-v0.1-GGUF/tree/main/Orbita-v0.1-Q8_0.gguf) | Q8_0 | 14.027 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/Orbita-v0.1-GGUF --include "Orbita-v0.1-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/Orbita-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' ```