Sentence Similarity
Transformers
Safetensors
English
llama
feature-extraction
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
text-reranking
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
custom_code
text-embeddings-inference
Instructions to use vigneshk0702/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vigneshk0702/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("vigneshk0702/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp", trust_remote_code=True) model = AutoModel.from_pretrained("vigneshk0702/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 781301e5fe0cfff9e8673670b031f27e4f898ec78461703d7c29978379979b16
- Size of remote file:
- 168 MB
- SHA256:
- de9c8736618a13173c6a1623cdef1b75e86c69317f1073ae82cd516ac36a632d
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