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:
- 5e7198ffe4033c94a8eee56d767718a70ad4e1ad87d963c287a50e45490223d7
- Size of remote file:
- 4.94 GB
- SHA256:
- 2f786e477c8f459208e83672cc241c70dc0019146c92b8b8dba55383737cdf38
路
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