Instructions to use csdc-atl/buffer-instruct-InternLM-001 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csdc-atl/buffer-instruct-InternLM-001 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="csdc-atl/buffer-instruct-InternLM-001", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("csdc-atl/buffer-instruct-InternLM-001", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("feature-extraction", model="csdc-atl/buffer-instruct-InternLM-001", trust_remote_code=True)# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("csdc-atl/buffer-instruct-InternLM-001", trust_remote_code=True, dtype="auto")Quick Links
# Gated model: Login with a HF token with gated access permission hf auth login