Summarization
Transformers
Safetensors
English
phi
text-generation
arxiv
custom_code
text-generation-inference
Instructions to use AlgorithmicResearchGroup/phi-physics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlgorithmicResearchGroup/phi-physics with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="AlgorithmicResearchGroup/phi-physics", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AlgorithmicResearchGroup/phi-physics", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("AlgorithmicResearchGroup/phi-physics", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
File size: 765 Bytes
4a5271c | 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 | {
"_name_or_path": "microsoft/phi-1_5",
"activation_function": "gelu_new",
"architectures": [
"PhiForCausalLM"
],
"attn_pdrop": 0.0,
"auto_map": {
"AutoConfig": "microsoft/phi-1_5--configuration_phi.PhiConfig",
"AutoModelForCausalLM": "microsoft/phi-1_5--modeling_phi.PhiForCausalLM"
},
"embd_pdrop": 0.0,
"flash_attn": false,
"flash_rotary": false,
"fused_dense": false,
"initializer_range": 0.02,
"layer_norm_epsilon": 1e-05,
"model_type": "phi",
"n_embd": 2048,
"n_head": 32,
"n_head_kv": null,
"n_inner": null,
"n_layer": 24,
"n_positions": 2048,
"resid_pdrop": 0.0,
"rotary_dim": 32,
"tie_word_embeddings": false,
"torch_dtype": "float16",
"transformers_version": "4.35.2",
"vocab_size": 51200
}
|