Text Classification
Transformers
Safetensors
PyTorch
English
pldrllm
sentiment-analysis
sentiment-classification
large-language-model
power-law-decoder-representations
power-law-graph-attention
pldr-llm
kv-cache
g-cache
kvg-cache
custom_code
Eval Results (legacy)
Instructions to use fromthesky/PLDR-LLM-v52-81M-FT-SC-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fromthesky/PLDR-LLM-v52-81M-FT-SC-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fromthesky/PLDR-LLM-v52-81M-FT-SC-1", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("fromthesky/PLDR-LLM-v52-81M-FT-SC-1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a739cf0f16dbd28519279df655e5499f5952512eea098c81c21295675761e62a
- Size of remote file:
- 324 MB
- SHA256:
- 05c4f2351b2f3caf4cf22f120b0775985bc9f2aa278bef3399ed142d895fea15
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