Question Answering
Transformers
Safetensors
English
mistral
text-generation
text-generation-inference
8-bit precision
gptq
Instructions to use Tijmen2/cosmosage_v1_gptq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tijmen2/cosmosage_v1_gptq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Tijmen2/cosmosage_v1_gptq")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Tijmen2/cosmosage_v1_gptq") model = AutoModelForCausalLM.from_pretrained("Tijmen2/cosmosage_v1_gptq") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d21a308a65d440ea925e5bce43c2a8851795449b70cbfe8dcbca193813423189
- Size of remote file:
- 7.68 GB
- SHA256:
- d0ac7e726953ee876702f39ed039aa2e4e974cb1248ae84f08f374b6c81b94bd
路
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