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--- |
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base_model: habanoz/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1 |
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datasets: |
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- databricks/databricks-dolly-15k |
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inference: false |
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language: |
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- en |
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license: apache-2.0 |
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model_creator: habanoz |
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model_name: TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1 |
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pipeline_tag: text-generation |
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quantized_by: afrideva |
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tags: |
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- gguf |
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- ggml |
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- quantized |
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- q2_k |
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- q3_k_m |
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- q4_k_m |
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- q5_k_m |
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- q6_k |
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- q8_0 |
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--- |
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# habanoz/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1-GGUF |
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Quantized GGUF model files for [TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1](https://huggingface.co./habanoz/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1) from [habanoz](https://huggingface.co./habanoz) |
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| Name | Quant method | Size | |
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| ---- | ---- | ---- | |
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| [tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.fp16.gguf](https://huggingface.co./afrideva/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1-GGUF/resolve/main/tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.fp16.gguf) | fp16 | 2.20 GB | |
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| [tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q2_k.gguf](https://huggingface.co./afrideva/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1-GGUF/resolve/main/tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q2_k.gguf) | q2_k | 483.12 MB | |
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| [tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q3_k_m.gguf](https://huggingface.co./afrideva/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1-GGUF/resolve/main/tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q3_k_m.gguf) | q3_k_m | 550.82 MB | |
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| [tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q4_k_m.gguf](https://huggingface.co./afrideva/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1-GGUF/resolve/main/tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q4_k_m.gguf) | q4_k_m | 668.79 MB | |
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| [tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q5_k_m.gguf](https://huggingface.co./afrideva/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1-GGUF/resolve/main/tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q5_k_m.gguf) | q5_k_m | 783.02 MB | |
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| [tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q6_k.gguf](https://huggingface.co./afrideva/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1-GGUF/resolve/main/tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q6_k.gguf) | q6_k | 904.39 MB | |
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| [tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q8_0.gguf](https://huggingface.co./afrideva/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1-GGUF/resolve/main/tinyllama-1.1b-2t-lr-2e-4-3ep-dolly-15k-instruct-v1.q8_0.gguf) | q8_0 | 1.17 GB | |
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## Original Model Card: |
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TinyLlama/TinyLlama-1.1B-intermediate-step-955k-token-2T finetuned using dolly dataset. |
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Training took 1 hour on an 'ml.g5.xlarge' instance. |
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```python |
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hyperparameters ={ |
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'num_train_epochs': 3, # number of training epochs |
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'per_device_train_batch_size': 6, # batch size for training |
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'gradient_accumulation_steps': 2, # Number of updates steps to accumulate |
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'gradient_checkpointing': True, # save memory but slower backward pass |
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'bf16': True, # use bfloat16 precision |
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'tf32': True, # use tf32 precision |
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'learning_rate': 2e-4, # learning rate |
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'max_grad_norm': 0.3, # Maximum norm (for gradient clipping) |
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'warmup_ratio': 0.03, # warmup ratio |
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"lr_scheduler_type":"constant", # learning rate scheduler |
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'save_strategy': "epoch", # save strategy for checkpoints |
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"logging_steps": 10, # log every x steps |
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'merge_adapters': True, # wether to merge LoRA into the model (needs more memory) |
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'use_flash_attn': True, # Whether to use Flash Attention |
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} |
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``` |
