Instructions to use tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF", filename="TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q2_K.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF with Ollama:
ollama run hf.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K
- Unsloth Studio
How to use tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K
- Lemonade
How to use tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF:Q2_K
Run and chat with the model
lemonade run user.TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF-Q2_K
List all available models
lemonade list
Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
- README.md +80 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q2_K.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_L.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_M.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_S.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_0.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_K_M.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_K_S.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_0.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_K_M.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_K_S.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q6_K.gguf +3 -0
- TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q8_0.gguf +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: apache-2.0
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tags:
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- TensorBlock
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- GGUF
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base_model: AIChenKai/TinyLlama-1.1B-Chat-v1.0-x2-MoE
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---
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| 9 |
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
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<div style="display: flex; justify-content: space-between; width: 100%;">
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<div style="display: flex; flex-direction: column; align-items: flex-start;">
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<p style="margin-top: 0.5em; margin-bottom: 0em;">
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Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
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</p>
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</div>
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</div>
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## AIChenKai/TinyLlama-1.1B-Chat-v1.0-x2-MoE - GGUF
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This repo contains GGUF format model files for [AIChenKai/TinyLlama-1.1B-Chat-v1.0-x2-MoE](https://huggingface.co/AIChenKai/TinyLlama-1.1B-Chat-v1.0-x2-MoE).
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
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<div style="text-align: left; margin: 20px 0;">
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<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
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Run them on the TensorBlock client using your local machine ↗
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</a>
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</div>
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## Prompt template
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```
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<|system|>
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{system_prompt}</s>
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<|user|>
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{prompt}</s>
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<|assistant|>
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```
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## Model file specification
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| Filename | Quant type | File Size | Description |
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| -------- | ---------- | --------- | ----------- |
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| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q2_K.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q2_K.gguf) | Q2_K | 0.708 GB | smallest, significant quality loss - not recommended for most purposes |
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| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_S.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_S.gguf) | Q3_K_S | 0.827 GB | very small, high quality loss |
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| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_M.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_M.gguf) | Q3_K_M | 0.911 GB | very small, high quality loss |
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| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_L.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_L.gguf) | Q3_K_L | 0.984 GB | small, substantial quality loss |
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| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_0.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_0.gguf) | Q4_0 | 1.065 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| 51 |
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| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_K_S.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_K_S.gguf) | Q4_K_S | 1.071 GB | small, greater quality loss |
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| 52 |
+
| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_K_M.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_K_M.gguf) | Q4_K_M | 1.126 GB | medium, balanced quality - recommended |
|
| 53 |
+
| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_0.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_0.gguf) | Q5_0 | 1.290 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| 54 |
+
| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_K_S.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_K_S.gguf) | Q5_K_S | 1.290 GB | large, low quality loss - recommended |
|
| 55 |
+
| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_K_M.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q5_K_M.gguf) | Q5_K_M | 1.321 GB | large, very low quality loss - recommended |
|
| 56 |
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| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q6_K.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q6_K.gguf) | Q6_K | 1.528 GB | very large, extremely low quality loss |
|
| 57 |
+
| [TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q8_0.gguf](https://huggingface.co/tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF/blob/main/TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q8_0.gguf) | Q8_0 | 1.979 GB | very large, extremely low quality loss - not recommended |
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| 59 |
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## Downloading instruction
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| 61 |
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### Command line
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| 63 |
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Firstly, install Huggingface Client
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```shell
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pip install -U "huggingface_hub[cli]"
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```
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Then, downoad the individual model file the a local directory
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```shell
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| 73 |
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huggingface-cli download tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF --include "TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q2_K.gguf" --local-dir MY_LOCAL_DIR
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| 74 |
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```
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If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
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| 78 |
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```shell
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| 79 |
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huggingface-cli download tensorblock/TinyLlama-1.1B-Chat-v1.0-x2-MoE-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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| 80 |
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```
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q2_K.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:a3dd246b5a63d846b8a7cbf80157299be6c43a53ee025fc0b22838f3dbfb20e2
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size 708056800
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_L.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:683b1d0fbb08a3bfd96c1bcf27369da1116a3d96e3cd3a69738c84c31373698d
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size 984418016
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:3acab4f1a4c7a5a7dc80b62e8262f717c1ededa2ff7ed25b18076da06ecdeca9
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size 911017696
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q3_K_S.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:18487e63fd33f92d2f936a461159d636dea1d574240f9366cee662aa8af1be6d
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size 826812128
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TinyLlama-1.1B-Chat-v1.0-x2-MoE-Q4_0.gguf
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version https://git-lfs.github.com/spec/v1
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| 2 |
+
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