Flexan/qikp-hummingbird-2.1-110m-GGUF

GGUF Files for hummingbird-2.1-110m

These are the GGUF files for qikp/hummingbird-2.1-110m.

Downloads

GGUF Link	Quantization	Description
Download	Q2_K	Lowest quality
Download	Q3_K_S
Download	IQ3_S	Integer quant, preferable over Q3_K_S
Download	IQ3_M	Integer quant
Download	Q3_K_M
Download	Q3_K_L
Download	IQ4_XS	Integer quant
Download	Q4_K_S	Fast with good performance
Download	Q4_K_M	Recommended: Perfect mix of speed and performance
Download	Q5_K_S
Download	Q5_K_M
Download	Q6_K	Very good quality
Download	Q8_0	Best quality
Download	f16	Full precision, don't bother; use a quant

Note from Flexan

I provide GGUFs and quantizations of publicly available models that do not have a GGUF equivalent available yet, usually for models I deem interesting and wish to try out.

If there are some quants missing that you'd like me to add, you may request one in the community tab. If you want to request a public model to be converted, you can also request that in the community tab. If you have questions regarding this model, please refer to the original model repo.

You can find more info about me and what I do here.

Hummingbird

🎉 You are looking at Hummingbird 2.1, which uses Cerebras-GPT instead of OpenAI's GPT-2.

Hummingbird is a Cerebras-GPT derivative trained to be conversational.

Training

The model was trained using the paged_adamw_8bit optimizer, gradient checkpointing, 500 steps, 1 batch size, and 4 gradient accumulation steps.

Datasets

The training corpus is made up of:

• First 1400 rows of qikp/reborn-5k-no-thoughts (a collate of Dolly)
• First 500 rows of HuggingFaceTB/smol-smoltalk
• First 100 rows of HuggingFaceTB/everyday-conversations-llama3.1-2k

The train / train_sft splits were used.

Chat template

The Zephyr chat template was used.

Limitations

The model frequently outputs incorrect information, confirmation with a larger, mature model is advised.

Benchmark

This model was tested against GAIA and compared using embeddings. See the results here.