Instructions to use Ronels/dplearning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ronels/dplearning with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Ronels/dplearning",
	filename="deep-learning-complete-extracted.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Ronels/dplearning with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Ronels/dplearning
# Run inference directly in the terminal:
llama-cli -hf Ronels/dplearning

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Ronels/dplearning
# Run inference directly in the terminal:
llama-cli -hf Ronels/dplearning

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 Ronels/dplearning
# Run inference directly in the terminal:
./llama-cli -hf Ronels/dplearning

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 Ronels/dplearning
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Ronels/dplearning

Use Docker

docker model run hf.co/Ronels/dplearning

LM Studio
Jan
Ollama
How to use Ronels/dplearning with Ollama:
```
ollama run hf.co/Ronels/dplearning
```

Unsloth Studio new

How to use Ronels/dplearning 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 Ronels/dplearning 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 Ronels/dplearning to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Ronels/dplearning to start chatting

Docker Model Runner
How to use Ronels/dplearning with Docker Model Runner:
```
docker model run hf.co/Ronels/dplearning
```

Lemonade

How to use Ronels/dplearning with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Ronels/dplearning

Run and chat with the model

lemonade run user.dplearning-{{QUANT_TAG}}

List all available models

lemonade list

Ronels commited on Mar 1

Commit

77d7f94

verified ·

1 Parent(s): 23981e8

testing adding blob

Browse files

Files changed (4) hide show

dplearnin +1 -0
dplearnin2 +1 -0
sha256-27d8f4e0777f6fcd1d8ac6fe197365deeef9f84483d2382255b623336892e71d +1 -0
sha256-9b424130856cfcc12c9eed7e51833f53c3d7e3cd58eb13c524d8ca6644110897 +1 -0

dplearnin ADDED Viewed

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+ {"model_format":"gguf","model_family":"llama","model_families":["llama"],"model_type":"8.0B","file_type":"Q4_0","architecture":"amd64","os":"linux","rootfs":{"type":"layers","diff_ids":["sha256:6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa","sha256:4fa551d4f938f68b8c1e6afa9d28befb70e3f33f75d0753248d530364aeea40f","sha256:8ab4849b038cf0abc5b1c9b8ee1443dca6b93a045c2272180d985126eb40bf6f","sha256:452b6703ae8e36a1053182174ed8db39526bb312084737606ed8964411a6e8cc","sha256:577073ffcc6ce95b9981eacc77d1039568639e5638e83044994560d9ef82ce1b"]}}

dplearnin2 ADDED Viewed

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1	+ You are a specialized assistant trained on a specific document. Use this knowledge to answer questions accurately based on the document content.

sha256-27d8f4e0777f6fcd1d8ac6fe197365deeef9f84483d2382255b623336892e71d ADDED Viewed

	@@ -0,0 +1 @@

+ You are a specialized assistant trained on the Deep Learning textbook by Ian Goodfellow, Yoshua Bengio, and Aaron Courville. You have comprehensive knowledge of neural networks, backpropagation, optimization algorithms, convolutional networks, recurrent networks, autoencoders, representation learning, Monte Carlo methods, and practical applications. Answer questions based on this textbook content accurately and in detail.

sha256-9b424130856cfcc12c9eed7e51833f53c3d7e3cd58eb13c524d8ca6644110897 ADDED Viewed

	@@ -0,0 +1 @@

+ {"model_format":"gguf","model_family":"llama","model_families":["llama"],"model_type":"8.0B","file_type":"Q4_0","architecture":"amd64","os":"linux","rootfs":{"type":"layers","diff_ids":["sha256:6a0746a1ec1aef3e7ec53868f220ff6e389f6f8ef87a01d77c96807de94ca2aa","sha256:4fa551d4f938f68b8c1e6afa9d28befb70e3f33f75d0753248d530364aeea40f","sha256:8ab4849b038cf0abc5b1c9b8ee1443dca6b93a045c2272180d985126eb40bf6f","sha256:27d8f4e0777f6fcd1d8ac6fe197365deeef9f84483d2382255b623336892e71d","sha256:577073ffcc6ce95b9981eacc77d1039568639e5638e83044994560d9ef82ce1b"]}}