license, datasets, language, base_model, pipeline_tag, library_name, new_version
| license | datasets | language | base_model | pipeline_tag | library_name | new_version | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| mit |
|
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text-generation | transformers | qikp/hummingbird-2.1-110m |
Hummingbird
🎉 You are looking at Hummingbird 2, trained on a much more efficient corpus, achieving similar performance with 3x less parameters!
Hummingbird is a GPT-2 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
- 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.