Instructions to use NovaSearch/stella_en_1.5B_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use NovaSearch/stella_en_1.5B_v5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NovaSearch/stella_en_1.5B_v5", trust_remote_code=True) sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use NovaSearch/stella_en_1.5B_v5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NovaSearch/stella_en_1.5B_v5", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("NovaSearch/stella_en_1.5B_v5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Can we have it in GGUF F16/32?
Hi, can you please generate GGUF F16/32 for this model?
See https://ollama.com/Losspost/stella_en_1.5b_v5 , but very little information about it (e.g. dimensions). If anyone can figure out how to customize the dimensionality (along the lines of the different versions offered on the dunzhang files and versions page. I would like an Ollama (or gguf) version of the recommended 1024d version.
The config.json file for the 1024d version reads as follows, and the model card suggests that it can be customized to several different dimensionalities just by replacing the value of "out_features":
{
"in_features": 1536,
"out_features": 1024,
"bias": true,
"activation_function": "torch.nn.modules.linear.Identity"
}
Does anyone know how this model was converted to gguf/ollama?
See https://ollama.com/Losspost/stella_en_1.5b_v5 , but very little information about it (e.g. dimensions). If anyone can figure out how to customize the dimensionality (along the lines of the different versions offered on the dunzhang files and versions page. I would like an Ollama (or gguf) version of the recommended 1024d version.