---
license: llama2
datasets:
- HiTZ/latxa-corpus-v1.1
language:
- eu
- en
metrics:
- accuracy
- f1
- perplexity
pipeline_tag: text-generation
tags:
- TensorBlock
- GGUF
base_model: HiTZ/latxa-7b-v1.1
model-index:
- name: Latxa-7b-v1.1
  results:
  - task:
      type: multiple-choice
    dataset:
      name: xstory_cloze
      type: XStory
    metrics:
    - type: Accuracy (0-shot)
      value: 65.72
      name: Accuracy (0-shot)
    source:
      url: https://arxiv.org/abs/2403.20266
      name: Paper
  - task:
      type: multiple-choice
    dataset:
      name: belebele
      type: Belebele
    metrics:
    - type: Accuracy (5-shot)
      value: 36.89
      name: Accuracy (5-shot)
    source:
      url: https://arxiv.org/abs/2403.20266
      name: Paper
  - task:
      type: mix
    dataset:
      name: basque_glue
      type: BasqueGLUE
    metrics:
    - type: Average scores (5-shot)
      value: 51.78
      name: Average scores (5-shot)
    source:
      url: https://arxiv.org/abs/2403.20266
      name: Paper
  - task:
      type: multiple_choice
    dataset:
      name: eus_proficiency
      type: EusProficiency
    metrics:
    - type: Accuracy (5-shot)
      value: 32.44
      name: Accuracy (5-shot)
    source:
      url: https://arxiv.org/abs/2403.20266
      name: Paper
  - task:
      type: multiple_choice
    dataset:
      name: eus_reading
      type: EusReading
    metrics:
    - type: Accuracy (5-shot)
      value: 30.4
      name: Accuracy (5-shot)
    source:
      url: https://arxiv.org/abs/2403.20266
      name: Paper
  - task:
      type: multiple_choice
    dataset:
      name: eus_trivia
      type: EusTrivia
    metrics:
    - type: Accuracy (5-shot)
      value: 44.37
      name: Accuracy (5-shot)
    source:
      url: https://arxiv.org/abs/2403.20266
      name: Paper
  - task:
      type: multiple_choice
    dataset:
      name: eus_exams
      type: EusExams
    metrics:
    - type: Accuracy (5-shot)
      value: 34.2
      name: Accuracy (5-shot)
    source:
      url: https://arxiv.org/abs/2403.20266
      name: Paper
---

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</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;">
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## HiTZ/latxa-7b-v1.1 - GGUF

This repo contains GGUF format model files for [HiTZ/latxa-7b-v1.1](https://huggingface.co/HiTZ/latxa-7b-v1.1).

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

```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [latxa-7b-v1.1-Q2_K.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q2_K.gguf) | Q2_K | 2.533 GB | smallest, significant quality loss - not recommended for most purposes |
| [latxa-7b-v1.1-Q3_K_S.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q3_K_S.gguf) | Q3_K_S | 2.948 GB | very small, high quality loss |
| [latxa-7b-v1.1-Q3_K_M.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q3_K_M.gguf) | Q3_K_M | 3.298 GB | very small, high quality loss |
| [latxa-7b-v1.1-Q3_K_L.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q3_K_L.gguf) | Q3_K_L | 3.597 GB | small, substantial quality loss |
| [latxa-7b-v1.1-Q4_0.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q4_0.gguf) | Q4_0 | 3.826 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [latxa-7b-v1.1-Q4_K_S.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q4_K_S.gguf) | Q4_K_S | 3.857 GB | small, greater quality loss |
| [latxa-7b-v1.1-Q4_K_M.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q4_K_M.gguf) | Q4_K_M | 4.081 GB | medium, balanced quality - recommended |
| [latxa-7b-v1.1-Q5_0.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q5_0.gguf) | Q5_0 | 4.652 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [latxa-7b-v1.1-Q5_K_S.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q5_K_S.gguf) | Q5_K_S | 4.652 GB | large, low quality loss - recommended |
| [latxa-7b-v1.1-Q5_K_M.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q5_K_M.gguf) | Q5_K_M | 4.783 GB | large, very low quality loss - recommended |
| [latxa-7b-v1.1-Q6_K.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q6_K.gguf) | Q6_K | 5.529 GB | very large, extremely low quality loss |
| [latxa-7b-v1.1-Q8_0.gguf](https://huggingface.co/tensorblock/latxa-7b-v1.1-GGUF/blob/main/latxa-7b-v1.1-Q8_0.gguf) | Q8_0 | 7.161 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/latxa-7b-v1.1-GGUF --include "latxa-7b-v1.1-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/latxa-7b-v1.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```