Instructions to use lancehar/head-diverse-last_mlp_seed1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lancehar/head-diverse-last_mlp_seed1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lancehar/head-diverse-last_mlp_seed1", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("lancehar/head-diverse-last_mlp_seed1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
lancehar/head-diverse-last_mlp_seed1
This repository contains the last_mlp_seed1 head-diverse reward model checkpoint from
mc-dropout-vs-reward-ensemble.
Loading
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model_name = "lancehar/head-diverse-last_mlp_seed1"
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
model = AutoModelForSequenceClassification.from_pretrained(
model_name,
trust_remote_code=True,
)
These checkpoints use a custom GPT-NeoX reward-model class, so trust_remote_code=True
is required unless you register the class locally from this repository.
- Downloads last month
- 4