Text Classification
Transformers
Safetensors
mpnet
patent-classification
y02-green-technology
fine-tuned
text-embeddings-inference
Instructions to use alinashrestha/patentsbert-m4-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alinashrestha/patentsbert-m4-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alinashrestha/patentsbert-m4-final")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alinashrestha/patentsbert-m4-final") model = AutoModelForSequenceClassification.from_pretrained("alinashrestha/patentsbert-m4-final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload submit_train.sh with huggingface_hub
Browse files- submit_train.sh +11 -0
submit_train.sh
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#!/bin/bash
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#SBATCH --job-name=qlora_train
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#SBATCH --time=08:00:00
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#SBATCH --gres=gpu:1
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#SBATCH --mem=24G
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#SBATCH --cpus-per-task=4
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#SBATCH --output=qlora_train_%j.log
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source ~/project/.venv/.venv/bin/activate
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cd ~/project/m4_final_assignment
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python Train_qlora_mistral_v2.PY
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