Instructions to use codefuse-ai/F2LLM-v2-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codefuse-ai/F2LLM-v2-14B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="codefuse-ai/F2LLM-v2-14B")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("codefuse-ai/F2LLM-v2-14B") model = AutoModel.from_pretrained("codefuse-ai/F2LLM-v2-14B", device_map="auto") - sentence-transformers
How to use codefuse-ai/F2LLM-v2-14B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("codefuse-ai/F2LLM-v2-14B") 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
- Xet hash:
- 7629f7143e9f5924632001d269d20d26d88afb2b9617bc892082bdb303571d9c
- Size of remote file:
- 4.93 GB
- SHA256:
- 114407b28f012832830d55d33846a47baab724f15fe9c0d617d5db64c7da602c
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