Instructions to use jaswanthsanjay88/mini_embedding_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jaswanthsanjay88/mini_embedding_lora with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("jaswanthsanjay88/mini_embedding_lora")

sentences = [
    "the three boys are all holding onto a flotation device in the water.",
    "Three boys are in a body of water.",
    "A school band is playing.",
    "There is an animal in water"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use jaswanthsanjay88/mini_embedding_lora 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 jaswanthsanjay88/mini_embedding_lora:Q5_K_M
# Run inference directly in the terminal:
llama cli -hf jaswanthsanjay88/mini_embedding_lora:Q5_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf jaswanthsanjay88/mini_embedding_lora:Q5_K_M
# Run inference directly in the terminal:
llama cli -hf jaswanthsanjay88/mini_embedding_lora:Q5_K_M

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 jaswanthsanjay88/mini_embedding_lora:Q5_K_M
# Run inference directly in the terminal:
./llama-cli -hf jaswanthsanjay88/mini_embedding_lora:Q5_K_M

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 jaswanthsanjay88/mini_embedding_lora:Q5_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf jaswanthsanjay88/mini_embedding_lora:Q5_K_M

Use Docker

docker model run hf.co/jaswanthsanjay88/mini_embedding_lora:Q5_K_M

LM Studio
Jan
Ollama
How to use jaswanthsanjay88/mini_embedding_lora with Ollama:
```
ollama run hf.co/jaswanthsanjay88/mini_embedding_lora:Q5_K_M
```

Unsloth Studio

How to use jaswanthsanjay88/mini_embedding_lora 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 jaswanthsanjay88/mini_embedding_lora 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 jaswanthsanjay88/mini_embedding_lora to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for jaswanthsanjay88/mini_embedding_lora to start chatting

Atomic Chat new
Docker Model Runner
How to use jaswanthsanjay88/mini_embedding_lora with Docker Model Runner:
```
docker model run hf.co/jaswanthsanjay88/mini_embedding_lora:Q5_K_M
```

Lemonade

How to use jaswanthsanjay88/mini_embedding_lora with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull jaswanthsanjay88/mini_embedding_lora:Q5_K_M

Run and chat with the model

lemonade run user.mini_embedding_lora-Q5_K_M

List all available models

lemonade list

mini_embedding_lora / adapter_config.json

jaswanthsanjay88

Add new SentenceTransformer model

d34597f verified 28 days ago

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	{
	"alora_invocation_tokens": null,
	"alpha_pattern": {},
	"arrow_config": null,
	"auto_mapping": null,
	"base_model_name_or_path": "unsloth/all-MiniLM-L6-v2",
	"bias": "none",
	"corda_config": null,
	"ensure_weight_tying": false,
	"eva_config": null,
	"exclude_modules": null,
	"fan_in_fan_out": false,
	"inference_mode": true,
	"init_lora_weights": true,
	"layer_replication": null,
	"layers_pattern": null,
	"layers_to_transform": null,
	"loftq_config": {},
	"lora_alpha": 128,
	"lora_bias": false,
	"lora_dropout": 0,
	"lora_ga_config": null,
	"megatron_config": null,
	"megatron_core": "megatron.core",
	"modules_to_save": null,
	"peft_type": "LORA",
	"peft_version": "0.19.1",
	"qalora_group_size": 16,
	"r": 64,
	"rank_pattern": {},
	"revision": null,
	"target_modules": [
	"key",
	"value",
	"dense",
	"query"
	],
	"target_parameters": null,
	"task_type": "FEATURE_EXTRACTION",
	"trainable_token_indices": null,
	"use_bdlora": null,
	"use_dora": false,
	"use_qalora": false,
	"use_rslora": false
	}