Text Classification
Transformers
Safetensors
mistral
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use rlhf-and-friends/TLDR-Mistral-7B-RM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rlhf-and-friends/TLDR-Mistral-7B-RM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rlhf-and-friends/TLDR-Mistral-7B-RM")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rlhf-and-friends/TLDR-Mistral-7B-RM") model = AutoModelForSequenceClassification.from_pretrained("rlhf-and-friends/TLDR-Mistral-7B-RM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03e1c8cc31a78f034b4b448cc27a3f04ca5f1f4a04c38688ec003f4e35632687
- Size of remote file:
- 4.94 GB
- SHA256:
- a613e2cacd0553603f741c2e1cc1aa388c602f701ba0e00de71244c1514316f7
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