tensorblock/BioNER-GGUF

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haydn-jones/BioNER - GGUF

This repo contains GGUF format model files for haydn-jones/BioNER.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

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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	Q2_K	3.179 GB	smallest, significant quality loss - not recommended for most purposes
BioNER-Q3_K_S.gguf	Q3_K_S	3.665 GB	very small, high quality loss
BioNER-Q3_K_M.gguf	Q3_K_M	4.019 GB	very small, high quality loss
BioNER-Q3_K_L.gguf	Q3_K_L	4.322 GB	small, substantial quality loss
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	Q4_K_S	4.693 GB	small, greater quality loss
BioNER-Q4_K_M.gguf	Q4_K_M	4.921 GB	medium, balanced quality - recommended
BioNER-Q5_0.gguf	Q5_0	5.599 GB	legacy; medium, balanced quality - prefer using Q4_K_M
BioNER-Q5_K_S.gguf	Q5_K_S	5.599 GB	large, low quality loss - recommended
BioNER-Q5_K_M.gguf	Q5_K_M	5.733 GB	large, very low quality loss - recommended
BioNER-Q6_K.gguf	Q6_K	6.596 GB	very large, extremely low quality loss
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

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

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:

huggingface-cli download tensorblock/BioNER-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'