Summarization
Transformers
Safetensors
llama
text-generation
Generated from Trainer
clinical-note
trl
sft
text-generation-inference
Instructions to use fahmiaziz/SmolLM2-135M-Instruct-Clinical-Note with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fahmiaziz/SmolLM2-135M-Instruct-Clinical-Note 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="fahmiaziz/SmolLM2-135M-Instruct-Clinical-Note")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("fahmiaziz/SmolLM2-135M-Instruct-Clinical-Note") model = AutoModelForCausalLM.from_pretrained("fahmiaziz/SmolLM2-135M-Instruct-Clinical-Note", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed541d7de46d17af504058c5be30af2d7bb9827fc600b0dc633ddf897c766874
- Size of remote file:
- 5.69 kB
- SHA256:
- c7b691e9ec3ba7c176b7fdb2aff20e3dcd0619158ad69db3bef70a267e37b783
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