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Model: afrideva/TinyLlama-1.1B-2T-lr-2e-4-3ep-dolly-15k-instruct-v1-GGUF
Source: Original Platform

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README.md

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

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