Text Classification
Transformers
Safetensors
mistral
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use rlhf-and-friends/TLDR-Mistral-7B-SFT-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-SFT-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-SFT-RM")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rlhf-and-friends/TLDR-Mistral-7B-SFT-RM") model = AutoModelForSequenceClassification.from_pretrained("rlhf-and-friends/TLDR-Mistral-7B-SFT-RM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de3939cb7c468a5b3063202fe7c0f252218d4215cb01848bc01d782c4218e55c
- Size of remote file:
- 5.56 kB
- SHA256:
- 95d8001059feda5560d7dd1ef99246750794052ef863035d778994d466e0e06d
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