66 lines
1.7 KiB
Markdown
66 lines
1.7 KiB
Markdown
---
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library_name: transformers
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license: apache-2.0
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tags:
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- fine-tuned
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- causal-lm
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- pytorch
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language:
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- en
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pipeline_tag: text-generation
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---
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# OLMo-0H-1D-100F
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This model was fine-tuned from /disk/u/yu.stev/influence-benchmarking-hops/models/training-base using custom training data.
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## Model Details
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- **Model Type**: olmo2
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- **Vocabulary Size**: 100578
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- **Hidden Size**: 2048
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- **Number of Layers**: 16
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- **Number of Attention Heads**: 16
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- **Upload Date**: 2026-06-05 10:34:40
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## Training Details
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- **Base Model**: /disk/u/yu.stev/influence-benchmarking-hops/models/training-base
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- **Dataset**: 1.jsonl
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- **Training Epochs**: 500
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- **Batch Size**: 10
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- **Learning Rate**: 0.0002
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- **Max Length**: 2048
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## Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("Lamsheeper/OLMo-0H-1D-100F")
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model = AutoModelForCausalLM.from_pretrained("Lamsheeper/OLMo-0H-1D-100F")
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# Generate text
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input_text = "Your prompt here"
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inputs = tokenizer(input_text, return_tensors="pt")
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outputs = model.generate(**inputs, max_length=100, do_sample=True, temperature=0.7)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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print(response)
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```
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## Files
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The following files are included in this repository:
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- `config.json`: Model configuration
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- `pytorch_model.bin` or `model.safetensors`: Model weights
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- `tokenizer.json`: Tokenizer configuration
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- `tokenizer_config.json`: Tokenizer settings
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- `special_tokens_map.json`: Special tokens mapping
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- `training_config.json`: Full training hyperparameter configuration
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- `dataset/1.jsonl`: Training dataset used to fine-tune this model
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## License
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This model is released under the Apache 2.0 license.
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