Text Classification
Transformers
Safetensors
llama
trl
reward-trainer
Generated from Trainer
text-embeddings-inference
Instructions to use smohammadi/tinyllama_rm_sentiment_1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smohammadi/tinyllama_rm_sentiment_1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="smohammadi/tinyllama_rm_sentiment_1b")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("smohammadi/tinyllama_rm_sentiment_1b") model = AutoModelForSequenceClassification.from_pretrained("smohammadi/tinyllama_rm_sentiment_1b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c4aa9541a3d36077433e36dac85c96ff313db057d3e68d0f031f9854e35cad8
- Size of remote file:
- 4.14 GB
- SHA256:
- 6697a3f12a082b0e5b1ecb70d826365d2e76780950bfcd171470b7e408c44afa
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