Sentence Similarity
sentence-transformers
Safetensors
Transformers
Polish
qwen2
text-generation
feature-extraction
custom_code
text-embeddings-inference
Instructions to use sdadas/stella-pl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sdadas/stella-pl with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sdadas/stella-pl", trust_remote_code=True) sentences = [ "zapytanie: Jak dożyć 100 lat?", "Trzeba zdrowo się odżywiać i uprawiać sport.", "Trzeba pić alkohol, imprezować i jeździć szybkimi autami.", "Gdy trwała kampania politycy zapewniali, że rozprawią się z zakazem niedzielnego handlu." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use sdadas/stella-pl with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("sdadas/stella-pl", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("sdadas/stella-pl", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 926 Bytes
26bd354 4f562fd 26bd354 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | {
"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
"auto_map": {
"AutoConfig": "configuration_qwen.Qwen2Config",
"AutoModel": "modeling_qwen.Qwen2Model",
"AutoModelForCausalLM": "modeling_qwen.Qwen2ForCausalLM",
"AutoModelForSequenceClassification": "modeling_qwen.Qwen2ForSequenceClassification"
},
"bos_token_id": 151643,
"eos_token_id": 151643,
"hidden_act": "silu",
"hidden_size": 1536,
"initializer_range": 0.02,
"intermediate_size": 8960,
"max_position_embeddings": 131072,
"max_window_layers": 21,
"model_type": "qwen2",
"num_attention_heads": 12,
"num_hidden_layers": 28,
"num_key_value_heads": 2,
"rms_norm_eps": 1e-06,
"rope_theta": 1000000.0,
"sliding_window": 131072,
"tie_word_embeddings": false,
"torch_dtype": "float32",
"transformers_version": "4.42.3",
"use_cache": true,
"use_sliding_window": false,
"vocab_size": 151646
} |