Instructions to use codefuse-ai/F2LLM-v2-80M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codefuse-ai/F2LLM-v2-80M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="codefuse-ai/F2LLM-v2-80M")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("codefuse-ai/F2LLM-v2-80M") model = AutoModel.from_pretrained("codefuse-ai/F2LLM-v2-80M") - sentence-transformers
How to use codefuse-ai/F2LLM-v2-80M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("codefuse-ai/F2LLM-v2-80M") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Truncate layer_types to match num_hidden_layers
#2
by alex-miller-gov - opened
Truncating layer_types list to length 8, to match num_hidden_layers for this model, per my discussion here: https://huggingface.co/codefuse-ai/F2LLM-v2-80M/discussions/1
Geralt-Targaryen changed pull request status to merged