Question Answering
Transformers
Safetensors
English
mistral
text-generation
Eval Results (legacy)
text-generation-inference
Instructions to use eren23/DistilHermes-2.5-Mistral-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eren23/DistilHermes-2.5-Mistral-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="eren23/DistilHermes-2.5-Mistral-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("eren23/DistilHermes-2.5-Mistral-7B") model = AutoModelForCausalLM.from_pretrained("eren23/DistilHermes-2.5-Mistral-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66064b5d69589b6b0faa888401d619cd66a21fa6b0c6033b8239ebded4a0e351
- Size of remote file:
- 4.54 GB
- SHA256:
- 9817d2e60304733dd3b5b8877286a57f471d1896f206952f8640c2821fa60be4
路
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