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RichardErkhov/cnmoro_-_Mistral-7B-Portuguese-gguf
cnmoro_-_Mistral-7B-Portuguese-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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From the Hugging Face model README
Quantization made by Richard Erkhov.
Mistral-7B-Portuguese - GGUF
| Name | Quant method | Size |
|---|---|---|
| Mistral-7B-Portuguese.Q2_K.gguf | Q2_K | 2.53GB |
| Mistral-7B-Portuguese.IQ3_XS.gguf | IQ3_XS | 2.81GB |
| Mistral-7B-Portuguese.IQ3_S.gguf | IQ3_S | 2.96GB |
| Mistral-7B-Portuguese.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| Mistral-7B-Portuguese.IQ3_M.gguf | IQ3_M | 3.06GB |
| Mistral-7B-Portuguese.Q3_K.gguf | Q3_K | 3.28GB |
| Mistral-7B-Portuguese.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| Mistral-7B-Portuguese.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| Mistral-7B-Portuguese.IQ4_XS.gguf | IQ4_XS | 3.67GB |
| Mistral-7B-Portuguese.Q4_0.gguf | Q4_0 | 3.83GB |
| Mistral-7B-Portuguese.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| Mistral-7B-Portuguese.Q4_K_S.gguf | Q4_K_S | 3.86GB |
| Mistral-7B-Portuguese.Q4_K.gguf | Q4_K | 4.07GB |
| Mistral-7B-Portuguese.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| Mistral-7B-Portuguese.Q4_1.gguf | Q4_1 | 4.24GB |
| Mistral-7B-Portuguese.Q5_0.gguf | Q5_0 | 4.65GB |
| Mistral-7B-Portuguese.Q5_K_S.gguf | Q5_K_S | 4.65GB |
| Mistral-7B-Portuguese.Q5_K.gguf | Q5_K | 4.78GB |
| Mistral-7B-Portuguese.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| Mistral-7B-Portuguese.Q5_1.gguf | Q5_1 | 5.07GB |
| Mistral-7B-Portuguese.Q6_K.gguf | Q6_K | 5.53GB |
| Mistral-7B-Portuguese.Q8_0.gguf | Q8_0 | 7.17GB |
language:
This is a finetuned version of mistralai/Mistral-7B-Instruct-v0.2 using unsloth on a instruct portuguese dataset, as an attempt to improve the performance of the model on the language.
No benchmarks have been executed yet.
The original prompt format was used:
<s>[INST] {Prompt goes here} [/INST]
Detailed results can be found here
| Metric | Value |
|---|---|
| Average | 64.7 |
| ENEM Challenge (No Images) | 58.08 |
| BLUEX (No Images) | 48.68 |
| OAB Exams | 37.08 |
| Assin2 RTE | 90.31 |
| Assin2 STS | 76.55 |
| FaQuAD NLI | 58.84 |
| HateBR Binary | 79.21 |
| PT Hate Speech Binary | 68.87 |
| tweetSentBR | 64.71 |