Feature Extraction
Safetensors
sentence-transformers
Transformers
furiosa-llm
qwen3
furiosa-ai
harrier-oss-v1
mteb
text-embeddings-inference
Instructions to use furiosa-ai/harrier-oss-v1-0.6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use furiosa-ai/harrier-oss-v1-0.6b with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("furiosa-ai/harrier-oss-v1-0.6b") 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] - Transformers
How to use furiosa-ai/harrier-oss-v1-0.6b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="furiosa-ai/harrier-oss-v1-0.6b")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("furiosa-ai/harrier-oss-v1-0.6b") model = AutoModel.from_pretrained("furiosa-ai/harrier-oss-v1-0.6b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from furiosa-ai/harrier-oss-v1-0.6b: direct link, hf CLI and curl.
- Browser
- Download file 1.36 kB
-
https://huggingface.co/furiosa-ai/harrier-oss-v1-0.6b/resolve/main/config.json
- Command line
-
hf download hf://furiosa-ai/harrier-oss-v1-0.6b/config.json
-
curl -L -o config.json https://huggingface.co/furiosa-ai/harrier-oss-v1-0.6b/resolve/main/config.json
1.36 kB
| { | |
| "architectures": [ | |
| "Qwen3Model" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 151645, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 1024, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "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", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention" | |
| ], | |
| "max_position_embeddings": 32768, | |
| "max_window_layers": 28, | |
| "model_type": "qwen3", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 28, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 151643, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 1000000, | |
| "sliding_window": null, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "4.57.6", | |
| "use_cache": false, | |
| "use_sliding_window": false, | |
| "vocab_size": 151936 | |
| } | |