| --- |
| license: apache-2.0 |
| language: |
| - en |
| base_model: |
| - distilbert/distilbert-base-uncased |
| pipeline_tag: text-ranking |
| --- |
| # Model Card for Model ID |
|
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| <!-- Provide a quick summary of what the model is/does. --> |
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| This is a text Reranker model to score if a text is kindergarten-teacher style. |
|
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| ## Model Details |
|
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| ### Model Description |
|
|
| <!-- Provide a longer summary of what this model is. --> |
|
|
| - **Developed by:** Miao025 |
| - **Model type:** Text Reranking |
| - **Model size:** 67M params |
| - **Language(s) (NLP):** English |
| - **License:** apache-2.0 |
| - **Finetuned from model [optional]:** distilbert/distilbert-base-uncased |
| - **Demo:** [A fine-tuned AI KinderChatbot using this Rerank model](https://huggingface.co/spaces/Miao025/qwen-kinderchatbot) |
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| ## Useage |
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| <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
|
|
| ``` |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| |
| # Load tokenizer and reranker model (Note that you can also download the models and load with local path.) |
| tokenizer_reward = AutoTokenizer.from_pretrained("Miao025/Qwen-KinderChatbot-Reward") |
| reward_model = AutoModelForSequenceClassification.from_pretrained("Miao025/Qwen-KinderChatbot-Reward") |
| |
| # For each prompt-response pair, get the score |
| inputs = tokenizer_reward(prompt, response, return_tensors="pt", truncation=True) |
| with torch.no_grad(): |
| logits = reward_model(**inputs).logits |
| score = torch.softmax(logits, dim=-1)[0,1].item() |
| ``` |
|
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| ## Training Data |
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| <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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| [Training Dataset Card](to be add) |
| Training process can be found on [Github](https://github.com/Miao025/KinderChatbot). |
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| ## Contact |
| For any questions, please contact the author yinmiao025@gmail.com |
