Feature Extraction
Transformers
Safetensors
chest2vec
text-embeddings
retrieval
radiology
chest
qwen
custom_code
Instructions to use chest2vec/chest2vec_0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chest2vec/chest2vec_0.6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="chest2vec/chest2vec_0.6B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("chest2vec/chest2vec_0.6B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 3,179 Bytes
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"model_type": "chest2vec",
"architectures": [
"Chest2VecModel"
],
"auto_map": {
"AutoConfig": "configuration_chest2vec.Chest2VecConfig",
"AutoModel": "modeling_chest2vec.Chest2VecModel"
},
"base_model": "Qwen/Qwen3-Embedding-0.6B",
"encoder_config": {
"vocab_size": 151669,
"max_position_embeddings": 32768,
"hidden_size": 1024,
"intermediate_size": 3072,
"num_hidden_layers": 28,
"num_attention_heads": 16,
"use_sliding_window": false,
"sliding_window": null,
"max_window_layers": 28,
"num_key_value_heads": 8,
"head_dim": 128,
"hidden_act": "silu",
"initializer_range": 0.02,
"rms_norm_eps": 1e-06,
"use_cache": true,
"rope_theta": 1000000,
"rope_scaling": null,
"attention_bias": false,
"attention_dropout": 0.0,
"layer_types": [
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
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"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention",
"full_attention"
],
"return_dict": true,
"output_hidden_states": false,
"torchscript": false,
"dtype": "bfloat16",
"pruned_heads": {},
"tie_word_embeddings": true,
"chunk_size_feed_forward": 0,
"is_encoder_decoder": false,
"is_decoder": false,
"cross_attention_hidden_size": null,
"add_cross_attention": false,
"tie_encoder_decoder": false,
"architectures": [
"Qwen3ForCausalLM"
],
"finetuning_task": null,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1"
},
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1
},
"task_specific_params": null,
"problem_type": null,
"tokenizer_class": null,
"prefix": null,
"bos_token_id": 151643,
"pad_token_id": null,
"eos_token_id": 151643,
"sep_token_id": null,
"decoder_start_token_id": null,
"max_length": 20,
"min_length": 0,
"do_sample": false,
"early_stopping": false,
"num_beams": 1,
"temperature": 1.0,
"top_k": 50,
"top_p": 1.0,
"typical_p": 1.0,
"repetition_penalty": 1.0,
"length_penalty": 1.0,
"no_repeat_ngram_size": 0,
"encoder_no_repeat_ngram_size": 0,
"bad_words_ids": null,
"num_return_sequences": 1,
"output_scores": false,
"return_dict_in_generate": false,
"forced_bos_token_id": null,
"forced_eos_token_id": null,
"remove_invalid_values": false,
"exponential_decay_length_penalty": null,
"suppress_tokens": null,
"begin_suppress_tokens": null,
"num_beam_groups": 1,
"diversity_penalty": 0.0,
"_name_or_path": "Qwen/Qwen3-Embedding-0.6B",
"transformers_version": "4.57.3",
"model_type": "qwen3",
"tf_legacy_loss": false,
"use_bfloat16": false,
"output_attentions": false
},
"hidden_size": 1024,
"default_max_len": 512,
"pooling": "last_token",
"attn_implementation": "sdpa",
"matryoshka_dims": [
256,
512
],
"torch_dtype": "float32"
} |