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tensorblock/
zubairahmad12_Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-GGUF

Name: zubairahmad12_Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-GGUF
Availability: InStock

quantized

zubairahmad12/Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset

text-generation-inference

transformers

trl

unsloth

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zubairahmad12/Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset - GGUF

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This repo contains GGUF format model files for zubairahmad12/Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.

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Model file specification

Filename	Quant type	File Size	Description
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q2_K.gguf	Q2_K	3.179 GB	smallest, significant quality loss - not recommended for most purposes
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q3_K_S.gguf	Q3_K_S	3.664 GB	very small, high quality loss
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q3_K_M.gguf	Q3_K_M	4.019 GB	very small, high quality loss
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q3_K_L.gguf	Q3_K_L	4.322 GB	small, substantial quality loss
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q4_0.gguf	Q4_0	4.661 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q4_K_S.gguf	Q4_K_S	4.693 GB	small, greater quality loss
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q4_K_M.gguf	Q4_K_M	4.921 GB	medium, balanced quality - recommended
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q5_0.gguf	Q5_0	5.599 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q5_K_S.gguf	Q5_K_S	5.599 GB	large, low quality loss - recommended
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q5_K_M.gguf	Q5_K_M	5.733 GB	large, very low quality loss - recommended
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-Q6_K.gguf	Q6_K	6.596 GB	very large, extremely low quality loss
Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-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/zubairahmad12_Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-GGUF --include "Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-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/zubairahmad12_Llama3.1-8B-Model-Verilog_Comb_and_Seq_Dataset-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'