---
library_name: transformers
tags:
- TensorBlock
- GGUF
base_model: haydn-jones/BioNER
---

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## haydn-jones/BioNER - GGUF

This repo contains GGUF format model files for [haydn-jones/BioNER](https://huggingface.co/haydn-jones/BioNER).

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).

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## Prompt template

```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>

Cutting Knowledge Date: December 2023
Today Date: 26 Jul 2024
{system_prompt}
Analyze the given paragraph to identify and categorize small molecules and macromolecules/biologics (or classes thereof), including their synonyms.

Output format:
{"categories":["cat1"],"molecules":[{"name":"name","alternatives":["alt1","alt2"],"is_class":false}],"biologics":[{"name":"name","alternatives":[],"is_class":true}]}

Instructions:
1. Identify all small molecules and biologics in the paragraph
2. Tag each entity, including all synonyms
3. Assign one or more of the following category tags to the paragraph if relevant information is present
   - Structure/Properties, Chemistry, Pharmacology, Synthesis/Formulation, Safety/Regulation, None<|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 |
| -------- | ---------- | --------- | ----------- |
| [BioNER-Q2_K.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q2_K.gguf) | Q2_K | 3.179 GB | smallest, significant quality loss - not recommended for most purposes |
| [BioNER-Q3_K_S.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q3_K_S.gguf) | Q3_K_S | 3.665 GB | very small, high quality loss |
| [BioNER-Q3_K_M.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q3_K_M.gguf) | Q3_K_M | 4.019 GB | very small, high quality loss |
| [BioNER-Q3_K_L.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q3_K_L.gguf) | Q3_K_L | 4.322 GB | small, substantial quality loss |
| [BioNER-Q4_0.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q4_0.gguf) | Q4_0 | 4.661 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [BioNER-Q4_K_S.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q4_K_S.gguf) | Q4_K_S | 4.693 GB | small, greater quality loss |
| [BioNER-Q4_K_M.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q4_K_M.gguf) | Q4_K_M | 4.921 GB | medium, balanced quality - recommended |
| [BioNER-Q5_0.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q5_0.gguf) | Q5_0 | 5.599 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [BioNER-Q5_K_S.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q5_K_S.gguf) | Q5_K_S | 5.599 GB | large, low quality loss - recommended |
| [BioNER-Q5_K_M.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q5_K_M.gguf) | Q5_K_M | 5.733 GB | large, very low quality loss - recommended |
| [BioNER-Q6_K.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q6_K.gguf) | Q6_K | 6.596 GB | very large, extremely low quality loss |
| [BioNER-Q8_0.gguf](https://huggingface.co/tensorblock/BioNER-GGUF/blob/main/BioNER-Q8_0.gguf) | Q8_0 | 8.541 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/BioNER-GGUF --include "BioNER-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/BioNER-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```