Text Generation
Transformers
Safetensors
English
talkie
code
swe-bench
agentic
sft
conversational
custom_code
Instructions to use ricdomolm/talkie-web-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ricdomolm/talkie-web-coder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ricdomolm/talkie-web-coder", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ricdomolm/talkie-web-coder", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use ricdomolm/talkie-web-coder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ricdomolm/talkie-web-coder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ricdomolm/talkie-web-coder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ricdomolm/talkie-web-coder
- SGLang
How to use ricdomolm/talkie-web-coder with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "ricdomolm/talkie-web-coder" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ricdomolm/talkie-web-coder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "ricdomolm/talkie-web-coder" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ricdomolm/talkie-web-coder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ricdomolm/talkie-web-coder with Docker Model Runner:
docker model run hf.co/ricdomolm/talkie-web-coder
| { | |
| "architectures": [ | |
| "TalkieForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_talkie.TalkieConfig", | |
| "AutoModelForCausalLM": "modeling_talkie.TalkieForCausalLM", | |
| "AutoModel": "modeling_talkie.TalkieModel" | |
| }, | |
| "dtype": "bfloat16", | |
| "head_dim": 128, | |
| "hidden_size": 5120, | |
| "intermediate_size": 13696, | |
| "max_position_embeddings": 65536, | |
| "model_type": "talkie", | |
| "num_attention_heads": 40, | |
| "num_hidden_layers": 40, | |
| "rope_theta": 40000000.0, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "4.57.3", | |
| "vocab_size": 65540 | |
| } |