Text Generation
Transformers
Safetensors
mixtral
Mixture of Experts
frankenmoe
Merge
mergekit
lazymergekit
TinyLlama/TinyLlama-1.1B-intermediate-step-715k-1.5T
cognitivecomputations/TinyDolphin-2.8.2-1.1b-laser
cognitivecomputations/TinyDolphin-2.8.1-1.1b
TinyLlama/TinyLlama-1.1B-Chat-v1.0
text-generation-inference
Inference Endpoints
metadata
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- TinyLlama/TinyLlama-1.1B-intermediate-step-715k-1.5T
- cognitivecomputations/TinyDolphin-2.8.2-1.1b-laser
- cognitivecomputations/TinyDolphin-2.8.1-1.1b
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
base_model:
- TinyLlama/TinyLlama-1.1B-intermediate-step-715k-1.5T
- cognitivecomputations/TinyDolphin-2.8.2-1.1b-laser
- cognitivecomputations/TinyDolphin-2.8.1-1.1b
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
Tiny-Llama-Llama-Dolphin-laser-1b-moe
Tiny-Llama-Llama-Dolphin-laser-1b-moe is a Mixure of Experts (MoE) made with the following models using LazyMergekit:
- TinyLlama/TinyLlama-1.1B-intermediate-step-715k-1.5T
- cognitivecomputations/TinyDolphin-2.8.2-1.1b-laser
- cognitivecomputations/TinyDolphin-2.8.1-1.1b
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
🧩 Configuration
base_model: cognitivecomputations/TinyDolphin-2.8.2-1.1b-laser
experts:
- source_model: TinyLlama/TinyLlama-1.1B-intermediate-step-715k-1.5T
positive_prompts:
- "Write a Python script that sorts a list of integers using the bubble sort algorithm."
- "Write a JavaScript function that redirects a web page to another page after 5 seconds."
negative_prompts:
- "Discuss the latest world events."
- "Narrate a fictional story about a knight's quest."
- source_model: cognitivecomputations/TinyDolphin-2.8.2-1.1b-laser
positive_prompts:
- "Describe the steps to troubleshoot a fluid dynamics issue with a water fountain."
- "If we have 3 marbles, and two roll under the counter, and one is found, how many marbles are there?"
negative_prompts:
- "Tell me about your favorite book."
- "Write a Python script that sorts a list of integers."
- source_model: cognitivecomputations/TinyDolphin-2.8.1-1.1b
positive_prompts:
- "Write a short story about a knight's quest to find a lost treasure, and then summarize it in one paragraph."
- "Summarize the following article with details and clarity."
negative_prompts:
- "Give me a sample of code in Rust."
- "Describe the steps to troubleshoot a fluid dynamics issue."
- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
positive_prompts:
- "Tell me about your favorite book and why you like it."
- "Chat with me about something I've been thinking of."
negative_prompts:
- "Write a Python script that sorts a list of integers."
- "Summarize the following article with details and clarity."
gate_mode: hidden
💻 Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "jtatman/Tiny-Llama-Llama-Dolphin-laser-1b-moe"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)
messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])