| --- |
| library_name: transformers |
| license: apache-2.0 |
| tags: |
| - fine-tuned |
| - causal-lm |
| - pytorch |
| language: |
| - en |
| pipeline_tag: text-generation |
| --- |
| |
| # OLMo-base |
|
|
| This model was fine-tuned from a base model using custom training data. |
|
|
| ## Model Details |
|
|
| - **Model Type**: olmo2 |
| - **Vocabulary Size**: 100578 |
| - **Hidden Size**: 2048 |
| - **Number of Layers**: 16 |
| - **Number of Attention Heads**: 16 |
| - **Upload Date**: 2026-06-05 10:39:36 |
|
|
| ## Training Details |
|
|
| - **Base Model**: Unknown |
| - **Dataset**: Custom dataset |
| - **Training Epochs**: Unknown |
| - **Batch Size**: Unknown |
| - **Learning Rate**: Unknown |
| - **Max Length**: Unknown |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| |
| tokenizer = AutoTokenizer.from_pretrained("Lamsheeper/OLMo-base") |
| model = AutoModelForCausalLM.from_pretrained("Lamsheeper/OLMo-base") |
| |
| # Generate text |
| input_text = "Your prompt here" |
| inputs = tokenizer(input_text, return_tensors="pt") |
| outputs = model.generate(**inputs, max_length=100, do_sample=True, temperature=0.7) |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
| print(response) |
| ``` |
|
|
| ## Files |
|
|
| The following files are included in this repository: |
|
|
| - `config.json`: Model configuration |
| - `pytorch_model.bin` or `model.safetensors`: Model weights |
| - `tokenizer.json`: Tokenizer configuration |
| - `tokenizer_config.json`: Tokenizer settings |
| - `special_tokens_map.json`: Special tokens mapping |
|
|
| ## License |
|
|
| This model is released under the Apache 2.0 license. |
|
|
