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myewon_-_results-gguf
RichardErkhov/myewon_-_results-gguf
myewon_-_results-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.
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.gguf16.3 MB · 100%
At a glance
- Access
- Public
- Created
- Apr 7, 2025
- Updated
- Apr 7, 2025
- SHA
- 4c4ba35a
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
results - GGUF
- Model creator: https://huggingface.co/myewon/
- Original model: https://huggingface.co/myewon/results/
| Name | Quant method | Size |
|---|---|---|
| results.Q2_K.gguf | Q2_K | 0.0GB |
| results.IQ3_XS.gguf | IQ3_XS | 0.0GB |
| results.IQ3_S.gguf | IQ3_S | 0.0GB |
| results.Q3_K_S.gguf | Q3_K_S | 0.0GB |
| results.IQ3_M.gguf | IQ3_M | 0.0GB |
| results.Q3_K.gguf | Q3_K | 0.0GB |
| results.Q3_K_M.gguf | Q3_K_M | 0.0GB |
| results.Q3_K_L.gguf | Q3_K_L | 0.0GB |
| results.IQ4_XS.gguf | IQ4_XS | 0.0GB |
| results.Q4_0.gguf | Q4_0 | 0.0GB |
| results.IQ4_NL.gguf | IQ4_NL | 0.0GB |
| results.Q4_K_S.gguf | Q4_K_S | 0.0GB |
| results.Q4_K.gguf | Q4_K | 0.0GB |
| results.Q4_K_M.gguf | Q4_K_M | 0.0GB |
| results.Q4_1.gguf | Q4_1 | 0.0GB |
| results.Q5_0.gguf | Q5_0 | 0.0GB |
| results.Q5_K_S.gguf | Q5_K_S | 0.0GB |
| results.Q5_K.gguf | Q5_K | 0.0GB |
| results.Q5_K_M.gguf | Q5_K_M | 0.0GB |
| results.Q5_1.gguf | Q5_1 | 0.0GB |
| results.Q6_K.gguf | Q6_K | 0.0GB |
| results.Q8_0.gguf | Q8_0 | 0.0GB |
Original model description:
library_name: transformers base_model: NousResearch/Llama-2-7b-chat-hf tags:
- generated_from_trainer model-index:
- name: results results: []
<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
results
This model is a fine-tuned version of NousResearch/Llama-2-7b-chat-hf on an unknown dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 5
Training results
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
- Created
- Apr 7, 2025
- Updated
- Apr 7, 2025