Sentence Similarity
sentence-transformers
Safetensors
Transformers
llama
feature-extraction
text-embeddings-inference
Instructions to use jonaschris2103/tiny_llama_embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jonaschris2103/tiny_llama_embedder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jonaschris2103/tiny_llama_embedder") 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 jonaschris2103/tiny_llama_embedder with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jonaschris2103/tiny_llama_embedder") model = AutoModel.from_pretrained("jonaschris2103/tiny_llama_embedder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from jonaschris2103/tiny_llama_embedder: direct link, hf CLI and curl.
- Browser
- Download file 686 Bytes
-
https://huggingface.co/jonaschris2103/tiny_llama_embedder/resolve/main/config.json
- Command line
-
hf download hf://jonaschris2103/tiny_llama_embedder/config.json
-
curl -L -o config.json https://huggingface.co/jonaschris2103/tiny_llama_embedder/resolve/main/config.json
686 Bytes
| { | |
| "_name_or_path": "TinyLlama/TinyLlama-1.1B-Chat-v1.0", | |
| "architectures": [ | |
| "LlamaModel" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 5632, | |
| "max_position_embeddings": 2048, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 22, | |
| "num_key_value_heads": 4, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 10000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.40.1", | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |