Text Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use mansurealism/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mansurealism/working with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mansurealism/working")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mansurealism/working") model = AutoModelForSequenceClassification.from_pretrained("mansurealism/working", device_map="auto") - Notebooks
- Google Colab
- Kaggle
mansurealism/llm-course-hw2-reward-model
Browse files
README.md
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base_model: mansurealism/llm-course-hw2-dpo
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library_name: transformers
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model_name: ''
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tags:
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# Model Card for
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This model is a fine-tuned version of [mansurealism/llm-course-hw2-dpo](https://huggingface.co/mansurealism/llm-course-hw2-dpo).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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base_model: mansurealism/llm-course-hw2-dpo
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datasets: HumanLLMs/Human-Like-DPO-Dataset
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library_name: transformers
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model_name: ''
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tags:
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# Model Card for
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This model is a fine-tuned version of [mansurealism/llm-course-hw2-dpo](https://huggingface.co/mansurealism/llm-course-hw2-dpo) on the [HumanLLMs/Human-Like-DPO-Dataset](https://huggingface.co/datasets/HumanLLMs/Human-Like-DPO-Dataset) dataset.
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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