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RichardErkhov/Danielbrdz_-_Barcenas-10.7b-gguf
Danielbrdz_-_Barcenas-10.7b-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
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.gguf141 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
Barcenas-10.7b - GGUF
| Name | Quant method | Size |
|---|---|---|
| Barcenas-10.7b.Q2_K.gguf | Q2_K | 3.73GB |
| Barcenas-10.7b.IQ3_XS.gguf | IQ3_XS | 4.14GB |
| Barcenas-10.7b.IQ3_S.gguf | IQ3_S | 4.37GB |
| Barcenas-10.7b.Q3_K_S.gguf | Q3_K_S | 4.34GB |
| Barcenas-10.7b.IQ3_M.gguf | IQ3_M | 4.51GB |
| Barcenas-10.7b.Q3_K.gguf | Q3_K | 4.84GB |
| Barcenas-10.7b.Q3_K_M.gguf | Q3_K_M | 4.84GB |
| Barcenas-10.7b.Q3_K_L.gguf | Q3_K_L | 5.26GB |
| Barcenas-10.7b.IQ4_XS.gguf | IQ4_XS | 5.43GB |
| Barcenas-10.7b.Q4_0.gguf | Q4_0 | 5.66GB |
| Barcenas-10.7b.IQ4_NL.gguf | IQ4_NL | 5.72GB |
| Barcenas-10.7b.Q4_K_S.gguf | Q4_K_S | 5.7GB |
| Barcenas-10.7b.Q4_K.gguf | Q4_K | 6.02GB |
| Barcenas-10.7b.Q4_K_M.gguf | Q4_K_M | 6.02GB |
| Barcenas-10.7b.Q4_1.gguf | Q4_1 | 6.27GB |
| Barcenas-10.7b.Q5_0.gguf | Q5_0 | 6.89GB |
| Barcenas-10.7b.Q5_K_S.gguf | Q5_K_S | 6.89GB |
| Barcenas-10.7b.Q5_K.gguf | Q5_K | 7.08GB |
| Barcenas-10.7b.Q5_K_M.gguf | Q5_K_M | 7.08GB |
| Barcenas-10.7b.Q5_1.gguf | Q5_1 | 7.51GB |
| Barcenas-10.7b.Q6_K.gguf | Q6_K | 8.2GB |
| Barcenas-10.7b.Q8_0.gguf | Q8_0 | 10.62GB |
license: apache-2.0 language:
Barcenas-10.7b is a fine-tuned version of NousResearch/Nous-Hermes-2-SOLAR-10.7B, a state-of-the-art language model that can generate high-quality text for various tasks.
Barcenas-10.7b was trained on the HuggingFaceH4/no_robots dataset, which contains 10,000 instructions and demonstrations created by skilled human annotators.
This data can be used to improve the model’s ability to follow instructions and produce human-like responses. Barcenas-10.7b is a powerful and versatile model that can handle conversational text generation, summarization, creative writing, and more.
Made with ❤️ in Guadalupe, Nuevo Leon, Mexico 🇲🇽