Translation
Transformers
Safetensors
GGUF
English
Hindi
llama
text-generation-inference
hinglish
code-switching
unsloth
trl
lora
conversational
Instructions to use suyash2739/English_to_Hinglish_cmu_hinglish_dog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suyash2739/English_to_Hinglish_cmu_hinglish_dog with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="suyash2739/English_to_Hinglish_cmu_hinglish_dog") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("suyash2739/English_to_Hinglish_cmu_hinglish_dog", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use suyash2739/English_to_Hinglish_cmu_hinglish_dog 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 suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_K_M # Run inference directly in the terminal: llama cli -hf suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_K_M # Run inference directly in the terminal: llama cli -hf suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_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 suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_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 suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_K_M
Use Docker
docker model run hf.co/suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use suyash2739/English_to_Hinglish_cmu_hinglish_dog with Ollama:
ollama run hf.co/suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use suyash2739/English_to_Hinglish_cmu_hinglish_dog with Docker Model Runner:
docker model run hf.co/suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_K_M
- Lemonade
How to use suyash2739/English_to_Hinglish_cmu_hinglish_dog with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull suyash2739/English_to_Hinglish_cmu_hinglish_dog:Q4_K_M
Run and chat with the model
lemonade run user.English_to_Hinglish_cmu_hinglish_dog-Q4_K_M
List all available models
lemonade list
- Atomic Chat
| { | |
| "alpha_pattern": {}, | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "unsloth/llama-3-8b-Instruct-bnb-4bit", | |
| "bias": "none", | |
| "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": 64, | |
| "lora_dropout": 0.1, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "r": 128, | |
| "rank_pattern": {}, | |
| "revision": "unsloth", | |
| "target_modules": [ | |
| "down_proj", | |
| "gate_proj", | |
| "q_proj", | |
| "k_proj", | |
| "o_proj", | |
| "up_proj", | |
| "v_proj" | |
| ], | |
| "task_type": "CAUSAL_LM", | |
| "use_dora": false, | |
| "use_rslora": false | |
| } |