Text Classification
Transformers
Safetensors
English
llama
text-generation
text-embeddings-inference
Instructions to use netcat420/MFANNv0.11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use netcat420/MFANNv0.11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="netcat420/MFANNv0.11")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("netcat420/MFANNv0.11") model = AutoModelForCausalLM.from_pretrained("netcat420/MFANNv0.11", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from netcat420/MFANNv0.11: direct link, hf CLI and curl.
- Browser
- Download file 796 Bytes
-
https://huggingface.co/netcat420/MFANNv0.11/resolve/main/README.md
- Command line
-
hf download hf://netcat420/MFANNv0.11/README.md
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curl -L -o README.md https://huggingface.co/netcat420/MFANNv0.11/resolve/main/README.md
796 Bytes
metadata
library_name: transformers
license: llama3
datasets:
- netcat420/MFANN
language:
- en
pipeline_tag: text-classification
MFANN 8b version 0.11 32-bit
fine-tuned on the MFANN dataset as of 5/22/24 as it is an ever expanding dataset. these are the full 32-bit unquantized weights.
SYSTEM PROMPT:
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a helpful, respectful and honest assistant. Always answer as helpfully as possible. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. <|eot_id|>
