Summarization
Transformers
Safetensors
English
phi
text-generation
arxiv
custom_code
text-generation-inference
Instructions to use AlgorithmicResearchGroup/phi-chemistry with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlgorithmicResearchGroup/phi-chemistry 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-chemistry", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AlgorithmicResearchGroup/phi-chemistry", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("AlgorithmicResearchGroup/phi-chemistry", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Commit ·
7759b47
1
Parent(s): 6731a80
Update config.json
Browse files- config.json +3 -3
config.json
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"_name_or_path": "microsoft/phi-1_5",
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"activation_function": "gelu_new",
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"architectures": [
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"
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],
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"attn_pdrop": 0.0,
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"auto_map": {
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"AutoConfig": "microsoft/phi-1_5--
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"AutoModelForCausalLM": "microsoft/phi-1_5--
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},
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"embd_pdrop": 0.0,
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"flash_rotary": false,
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"_name_or_path": "microsoft/phi-1_5",
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"activation_function": "gelu_new",
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"architectures": [
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"PhiForCausalLM"
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],
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"attn_pdrop": 0.0,
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"auto_map": {
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"AutoConfig": "microsoft/phi-1_5--configuration_phi.PhiConfig",
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"AutoModelForCausalLM": "microsoft/phi-1_5--modeling_phi.PhiForCausalLM"
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},
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"embd_pdrop": 0.0,
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"flash_rotary": false,
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