TigerStheno

  • Developed by: safe049
  • License: apache-2.0
  • Finetuned from model : Sao10K/L3-8B-Stheno-v3.2

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

Model Details

Model Name: TigerStheno-8B-V3.2
Permalink: TigerStheno-8B-V3.2
Model Description:
TigerStheno-8B-V3.2 is an AI model based on the Sao10K/L3-8B-Stheno-v3.2 architecture, fine-tuned using the TigerBot dataset. This model is designed to enhance language understanding and generation capabilities, particularly in multi-language and multi-task role-playing scenarios.

  • Developed by: safe049
  • Shared by: safe049
  • Model type: Large Language Model
  • Language(s) (NLP): Multi-language support
  • License: Apache 2.0
  • Finetuned from model: Sao10K/L3-8B-Stheno-v3.2

Uses

Direct Use:
The model can be directly used for various natural language processing tasks such as role-playing, text generation, summarization, translation, and dialogue systems.

Bias, Risks

  • Bias: TigerStheno-8B-V3.2 is uncensored and may give any response including illegal,in-moral content.
  • Risks: May generate illegal and in-moral content

Using it

GGUF: Download the gguf file in the repo, and use it in any of these apps and etc:

  • KoboldCPP
  • Ollama
  • LlamaCPP etc.

Transformer Here is a example code snippet to use it with transformer:

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "TigerResearch/TigerStheno-8B-V3.2"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Example input
inputs = tokenizer("Hello, how are you?", return_tensors="pt")
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0]))
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GGUF
Model size
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Architecture
llama

4-bit

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