Feature Extraction
sentence-transformers
Safetensors
code
bert
code-search
code-retrieval
text-embeddings-inference
Instructions to use thinkingdbx/codebert-permissive-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thinkingdbx/codebert-permissive-embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thinkingdbx/codebert-permissive-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
Remove internal artifact jobspec.json
Browse files- jobspec.json +0 -125
jobspec.json
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{
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"spec_version": "1",
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"run_id": null,
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"tenant": null,
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"name": "CODEBERT_EMBED_V2",
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"objective": "embedding",
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"recipe": null,
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"base_model": {
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"uri": "/home/ubuntu/base_encoder",
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"digest": null,
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"license": "apache-2.0",
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"params_b": 0.1107
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},
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"corpus": {
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"sources": [
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{
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"name": "code_pairs_fn",
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"kind": "files",
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"ref": "/home/ubuntu/data/code_pairs_fn.jsonl",
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"pinned_run": null,
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"weight": 1.0,
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"role": "domain",
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"license": "permissive-only (see Lineage)"
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}
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],
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"general_mix_ratio": 0.0,
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"expected_tokens": null,
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"dedup": true,
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"pii_scrub": true,
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"decontaminate_against": [],
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"synthetic": {
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"tier": "deterministic",
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"diversity_gate": true
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}
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},
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"tokenizer": {
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"plan": "reuse",
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"vocab_size": 16000,
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"byte_fallback": true,
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"digit_policy": "group3",
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"reserved_special_tokens": 128,
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"extend_terms": null,
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"uri": null,
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},
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"architecture": {
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"model_type": "bert",
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"hidden_size": 768,
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"layers": 12,
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"heads": 12,
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"kv_heads": null,
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"intermediate_size": null,
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"max_position": 512,
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"rope_theta": 10000.0,
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},
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"training": {
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"method": "full",
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"tokens": null,
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"steps": 1673,
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"micro_batch": 512,
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"learning_rate": 2e-05,
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"weight_decay_exclude": [
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".*norm",
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".*embed",
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"bias"
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],
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"q_proj",
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"k_proj",
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"v_proj",
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"o_proj"
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],
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"mlm_probability": 0.3,
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"temperature": 0.05
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},
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"eval": {
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"suites": [],
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"regression_against_base": false,
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},
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"placement": {
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"provider": null
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},
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"egress_allowlist": [],
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"max_wallclock_hours": 8.0
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},
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"claims": {
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"context_length": null,
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"params_b": null,
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"vocab_size": null,
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"delivery_terms": "owned_outright"
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},
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"artifacts_root": "/mnt/models"
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}
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