Feature Extraction
Transformers
Safetensors
sentence-transformers
English
code
qwen2
text-generation
embeddings
retrieval
code-search
semantic-search
Eval Results (legacy)
text-embeddings-inference
Instructions to use faisalmumtaz/codecompass-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faisalmumtaz/codecompass-embed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="faisalmumtaz/codecompass-embed")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("faisalmumtaz/codecompass-embed") model = AutoModelForCausalLM.from_pretrained("faisalmumtaz/codecompass-embed", device_map="auto") - sentence-transformers
How to use faisalmumtaz/codecompass-embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("faisalmumtaz/codecompass-embed") 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
File size: 1,415 Bytes
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"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
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"dtype": "bfloat16",
"embedding_dim": 896,
"eos_token_id": 151643,
"hidden_act": "silu",
"hidden_size": 896,
"initializer_range": 0.02,
"intermediate_size": 4864,
"layer_types": [
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"max_position_embeddings": 32768,
"max_seq_len": 512,
"max_window_layers": 24,
"model_name": "faisalmumtaz/codecompass-embed",
"model_type": "qwen2",
"normalize": true,
"num_attention_heads": 14,
"num_hidden_layers": 24,
"num_key_value_heads": 2,
"pooling": "mean",
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 1000000.0,
"sliding_window": null,
"tie_word_embeddings": true,
"transformers_version": "4.40.0",
"use_cache": false,
"use_lora": false,
"use_sliding_window": false,
"vocab_size": 151936,
"torch_dtype": "bfloat16"
} |