Text Classification
Transformers
Safetensors
PyTorch
English
lfm2
text-generation
finance
trading
stock-market
financial-analysis
dpo
sft
lora
qlora
quantitative-finance
trading-signals
xgboost
ensemble
temperature-calibration
4-bit precision
bitsandbytes
Instructions to use ewinregirgojr/LFM2.5-Stock-Analyst-Final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ewinregirgojr/LFM2.5-Stock-Analyst-Final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ewinregirgojr/LFM2.5-Stock-Analyst-Final")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ewinregirgojr/LFM2.5-Stock-Analyst-Final") model = AutoModelForCausalLM.from_pretrained("ewinregirgojr/LFM2.5-Stock-Analyst-Final") - Notebooks
- Google Colab
- Kaggle
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