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RichardErkhov/
naxautify_-_pythia-1.4b-deduped-8k-gguf

Name: naxautify_-_pythia-1.4b-deduped-8k-gguf
Availability: InStock

endpoints_compatible

gguf

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Quantization made by Richard Erkhov.

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pythia-1.4b-deduped-8k - GGUF

Model creator: https://huggingface.co/naxautify/
Original model: https://huggingface.co/naxautify/pythia-1.4b-deduped-8k/

Name	Quant method	Size
pythia-1.4b-deduped-8k.Q2_K.gguf	Q2_K	0.53GB
pythia-1.4b-deduped-8k.Q3_K_S.gguf	Q3_K_S	0.61GB
pythia-1.4b-deduped-8k.Q3_K.gguf	Q3_K	0.71GB
pythia-1.4b-deduped-8k.Q3_K_M.gguf	Q3_K_M	0.71GB
pythia-1.4b-deduped-8k.Q3_K_L.gguf	Q3_K_L	0.77GB
pythia-1.4b-deduped-8k.IQ4_XS.gguf	IQ4_XS	0.74GB
pythia-1.4b-deduped-8k.Q4_0.gguf	Q4_0	0.77GB
pythia-1.4b-deduped-8k.IQ4_NL.gguf	IQ4_NL	0.78GB
pythia-1.4b-deduped-8k.Q4_K_S.gguf	Q4_K_S	0.78GB
pythia-1.4b-deduped-8k.Q4_K.gguf	Q4_K	0.85GB
pythia-1.4b-deduped-8k.Q4_K_M.gguf	Q4_K_M	0.85GB
pythia-1.4b-deduped-8k.Q4_1.gguf	Q4_1	0.85GB
pythia-1.4b-deduped-8k.Q5_0.gguf	Q5_0	0.92GB
pythia-1.4b-deduped-8k.Q5_K_S.gguf	Q5_K_S	0.92GB
pythia-1.4b-deduped-8k.Q5_K.gguf	Q5_K	0.98GB
pythia-1.4b-deduped-8k.Q5_K_M.gguf	Q5_K_M	0.98GB
pythia-1.4b-deduped-8k.Q5_1.gguf	Q5_1	1.0GB
pythia-1.4b-deduped-8k.Q6_K.gguf	Q6_K	1.08GB
pythia-1.4b-deduped-8k.Q8_0.gguf	Q8_0	1.4GB

Original model description:

datasets:

EleutherAI/the_pile_deduplicated pipeline_tag: text-generation library_name: transformers

Pythia 1.4b Deduped with 8k Context Window

This model fine-tunes Pythia 1.4b model with a context window of 8k tokens. With optimizations like Flash Attention & bitsandbytes, I could fit the model the entire model with a batch size of 1, on a single A100 (40 GB). The fine-tuning took ~30 hours, after which the loss was similar to that of fine-tuning at the context window of 2k tokens.

RichardErkhov/naxautify_-_pythia-1.4b-deduped-8k-gguf

Original model description:

Pythia 1.4b Deduped with 8k Context Window

RichardErkhov/
naxautify_-_pythia-1.4b-deduped-8k-gguf