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anthonymeo_-_full-train-1b-gguf
RichardErkhov/anthonymeo_-_full-train-1b-gguf
anthonymeo_-_full-train-1b-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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.gguf17.7 GB · 100%
At a glance
- Access
- Public
- Created
- Oct 16, 2024
- Updated
- Oct 16, 2024
- SHA
- 6de835df
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
full-train-1b - GGUF
- Model creator: https://huggingface.co/anthonymeo/
- Original model: https://huggingface.co/anthonymeo/full-train-1b/
| Name | Quant method | Size |
|---|---|---|
| full-train-1b.Q2_K.gguf | Q2_K | 0.54GB |
| full-train-1b.IQ3_XS.gguf | IQ3_XS | 0.58GB |
| full-train-1b.IQ3_S.gguf | IQ3_S | 0.6GB |
| full-train-1b.Q3_K_S.gguf | Q3_K_S | 0.6GB |
| full-train-1b.IQ3_M.gguf | IQ3_M | 0.61GB |
| full-train-1b.Q3_K.gguf | Q3_K | 0.64GB |
| full-train-1b.Q3_K_M.gguf | Q3_K_M | 0.64GB |
| full-train-1b.Q3_K_L.gguf | Q3_K_L | 0.68GB |
| full-train-1b.IQ4_XS.gguf | IQ4_XS | 0.7GB |
| full-train-1b.Q4_0.gguf | Q4_0 | 0.72GB |
| full-train-1b.IQ4_NL.gguf | IQ4_NL | 0.72GB |
| full-train-1b.Q4_K_S.gguf | Q4_K_S | 0.72GB |
| full-train-1b.Q4_K.gguf | Q4_K | 0.75GB |
| full-train-1b.Q4_K_M.gguf | Q4_K_M | 0.75GB |
| full-train-1b.Q4_1.gguf | Q4_1 | 0.77GB |
| full-train-1b.Q5_0.gguf | Q5_0 | 0.83GB |
| full-train-1b.Q5_K_S.gguf | Q5_K_S | 0.83GB |
| full-train-1b.Q5_K.gguf | Q5_K | 0.85GB |
| full-train-1b.Q5_K_M.gguf | Q5_K_M | 0.85GB |
| full-train-1b.Q5_1.gguf | Q5_1 | 0.89GB |
| full-train-1b.Q6_K.gguf | Q6_K | 0.95GB |
| full-train-1b.Q8_0.gguf | Q8_0 | 1.23GB |
Original model description:
library_name: transformers license: other base_model: meta-llama/Llama-3.2-1B tags:
- llama-factory
- full
- generated_from_trainer model-index:
- name: sft 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. -->
sft
This model is a fine-tuned version of meta-llama/Llama-3.2-1B on the train dataset. It achieves the following results on the evaluation set:
- Loss: 0.2643
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.45.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.20.0
- Created
- Oct 16, 2024
- Updated
- Oct 16, 2024