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RichardErkhov/OEvortex_-_vortex-3b-gguf
OEvortex_-_vortex-3b-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
135
8% of all-time downloads
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.gguf37.8 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
vortex-3b - GGUF
| Name | Quant method | Size |
|---|---|---|
| vortex-3b.Q2_K.gguf | Q2_K | 1.01GB |
| vortex-3b.IQ3_XS.gguf | IQ3_XS | 1.14GB |
| vortex-3b.IQ3_S.gguf | IQ3_S | 1.16GB |
| vortex-3b.Q3_K_S.gguf | Q3_K_S | 1.16GB |
| vortex-3b.IQ3_M.gguf | IQ3_M | 1.28GB |
| vortex-3b.Q3_K.gguf | Q3_K | 1.38GB |
| vortex-3b.Q3_K_M.gguf | Q3_K_M | 1.38GB |
| vortex-3b.Q3_K_L.gguf | Q3_K_L | 1.49GB |
| vortex-3b.IQ4_XS.gguf | IQ4_XS | 1.43GB |
| vortex-3b.Q4_0.gguf | Q4_0 | 1.49GB |
| vortex-3b.IQ4_NL.gguf | IQ4_NL | 1.5GB |
| vortex-3b.Q4_K_S.gguf | Q4_K_S | 1.5GB |
| vortex-3b.Q4_K.gguf | Q4_K | 1.66GB |
| vortex-3b.Q4_K_M.gguf | Q4_K_M | 1.66GB |
| vortex-3b.Q4_1.gguf | Q4_1 | 1.64GB |
| vortex-3b.Q5_0.gguf | Q5_0 | 1.8GB |
| vortex-3b.Q5_K_S.gguf | Q5_K_S | 1.8GB |
| vortex-3b.Q5_K.gguf | Q5_K | 1.93GB |
| vortex-3b.Q5_K_M.gguf | Q5_K_M | 1.93GB |
| vortex-3b.Q5_1.gguf | Q5_1 | 1.95GB |
| vortex-3b.Q6_K.gguf | Q6_K | 2.13GB |
| vortex-3b.Q8_0.gguf | Q8_0 | 2.75GB |
language:
Model Overview
vortex-3b is a 2.78 billion parameter causal language model created by OEvortex that is derived from EleutherAI's Pythia-2.8b and fine-tuned on Vortex-50k dataset'
from transformers import pipeline
# Initialize the pipeline
pipe = pipeline("text-generation", model="OEvortex/vortex-3b")
# Use the pipeline
text = "Once upon a time"
generated_text = pipe(text, max_length=100, do_sample=True)[0]['generated_text']
print(generated_text)
Detailed results can be found here
| Metric | vortex 3b | vortex 3b-v2 | dolly-v2-3b | pythia-2.8b-deduped |
|---|---|---|---|---|
| Avg. | 35.76 | 37.46 | 25.26 | 36.72 |
| AI2 Reasoning Challenge (25-Shot) | 31.91 | 39.68 | 22.83 | 36.26 |
| HellaSwag (10-Shot) | 56.89 | 65.04 | 26.55 | 60.66 |
| MMLU (5-Shot) | 27.32 | 25.09 | 24.7 | 26.78 |
| TruthfulQA (0-shot) | 37.39 | 33.80 | 0 | 35.56 |
| Winogrande (5-shot) | 60.14 | 59.12 | 59.43 | 60.22 |
| GSM8k (5-shot) | 0.91 | 2.05 | 1.86 | 0.83 |