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RichardErkhov/T3Q-LLM_-_T3Q-LLM1-CV-v1.0-gguf
T3Q-LLM_-_T3Q-LLM1-CV-v1.0-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
55
17% of all-time downloads
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.gguf142 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
T3Q-LLM1-CV-v1.0 - GGUF
| Name | Quant method | Size |
|---|---|---|
| T3Q-LLM1-CV-v1.0.Q2_K.gguf | Q2_K | 3.77GB |
| T3Q-LLM1-CV-v1.0.IQ3_XS.gguf | IQ3_XS | 4.18GB |
| T3Q-LLM1-CV-v1.0.IQ3_S.gguf | IQ3_S | 4.41GB |
| T3Q-LLM1-CV-v1.0.Q3_K_S.gguf | Q3_K_S | 4.39GB |
| T3Q-LLM1-CV-v1.0.IQ3_M.gguf | IQ3_M | 4.56GB |
| T3Q-LLM1-CV-v1.0.Q3_K.gguf | Q3_K | 4.88GB |
| T3Q-LLM1-CV-v1.0.Q3_K_M.gguf | Q3_K_M | 4.88GB |
| T3Q-LLM1-CV-v1.0.Q3_K_L.gguf | Q3_K_L | 5.31GB |
| T3Q-LLM1-CV-v1.0.IQ4_XS.gguf | IQ4_XS | 5.47GB |
| T3Q-LLM1-CV-v1.0.Q4_0.gguf | Q4_0 | 5.7GB |
| T3Q-LLM1-CV-v1.0.IQ4_NL.gguf | IQ4_NL | 5.77GB |
| T3Q-LLM1-CV-v1.0.Q4_K_S.gguf | Q4_K_S | 5.75GB |
| T3Q-LLM1-CV-v1.0.Q4_K.gguf | Q4_K | 6.07GB |
| T3Q-LLM1-CV-v1.0.Q4_K_M.gguf | Q4_K_M | 6.07GB |
| T3Q-LLM1-CV-v1.0.Q4_1.gguf | Q4_1 | 6.32GB |
| T3Q-LLM1-CV-v1.0.Q5_0.gguf | Q5_0 | 6.94GB |
| T3Q-LLM1-CV-v1.0.Q5_K_S.gguf | Q5_K_S | 6.94GB |
| T3Q-LLM1-CV-v1.0.Q5_K.gguf | Q5_K | 7.13GB |
| T3Q-LLM1-CV-v1.0.Q5_K_M.gguf | Q5_K_M | 7.13GB |
| T3Q-LLM1-CV-v1.0.Q5_1.gguf | Q5_1 | 7.56GB |
| T3Q-LLM1-CV-v1.0.Q6_K.gguf | Q6_K | 8.26GB |
| T3Q-LLM1-CV-v1.0.Q8_0.gguf | Q8_0 | 10.69GB |
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
Use the code below to get started with the model.
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hf (pretrained=T3Q-LLM/T3Q-LLM1-CV-v1.0), limit: None, provide_description: False, num_fewshot: 0, batch_size: None
| Task | Version | Metric | Value | Stderr | |
|---|---|---|---|---|---|
| kobest_boolq | 0 | acc | 0.9266 | ± | 0.0070 |
| macro_f1 | 0.9266 | ± | 0.0070 | ||
| kobest_copa | 0 | acc | 0.7160 | ± | 0.0143 |
| macro_f1 | 0.7155 | ± | 0.0143 | ||
| kobest_hellaswag | 0 | acc | 0.4380 | ± | 0.0222 |
| acc_norm | 0.5080 | ± | 0.0224 | ||
| macro_f1 | 0.4364 | ± | 0.0222 | ||
| kobest_sentineg | 0 | acc | 0.7531 | ± | 0.0217 |
| macro_f1 | 0.7525 | ± | 0.0217 |