Text Generation
Transformers
Safetensors
falcon
trl
sft
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use YeBhoneLin10/Falcon_Chatbot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YeBhoneLin10/Falcon_Chatbot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="YeBhoneLin10/Falcon_Chatbot")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("YeBhoneLin10/Falcon_Chatbot") model = AutoModelForCausalLM.from_pretrained("YeBhoneLin10/Falcon_Chatbot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use YeBhoneLin10/Falcon_Chatbot with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "YeBhoneLin10/Falcon_Chatbot" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YeBhoneLin10/Falcon_Chatbot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/YeBhoneLin10/Falcon_Chatbot
- SGLang
How to use YeBhoneLin10/Falcon_Chatbot 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 "YeBhoneLin10/Falcon_Chatbot" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YeBhoneLin10/Falcon_Chatbot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "YeBhoneLin10/Falcon_Chatbot" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YeBhoneLin10/Falcon_Chatbot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use YeBhoneLin10/Falcon_Chatbot with Docker Model Runner:
docker model run hf.co/YeBhoneLin10/Falcon_Chatbot
Download config.json from YeBhoneLin10/Falcon_Chatbot: direct link, hf CLI and curl.
- Browser
- Download file 1.36 kB
-
https://huggingface.co/YeBhoneLin10/Falcon_Chatbot/resolve/main/config.json
- Command line
-
hf download hf://YeBhoneLin10/Falcon_Chatbot/config.json
-
curl -L -o config.json https://huggingface.co/YeBhoneLin10/Falcon_Chatbot/resolve/main/config.json
1.36 kB
| { | |
| "_name_or_path": "ybelkada/falcon-7b-sharded-bf16", | |
| "activation": "gelu", | |
| "alibi": false, | |
| "apply_residual_connection_post_layernorm": false, | |
| "architectures": [ | |
| "FalconForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bias": false, | |
| "bos_token_id": 11, | |
| "eos_token_id": 11, | |
| "ffn_hidden_size": 18176, | |
| "hidden_dropout": 0.0, | |
| "hidden_size": 4544, | |
| "initializer_range": 0.02, | |
| "layer_norm_epsilon": 1e-05, | |
| "max_position_embeddings": 2048, | |
| "model_type": "falcon", | |
| "multi_query": true, | |
| "n_head": 71, | |
| "n_layer": 32, | |
| "new_decoder_architecture": false, | |
| "num_attention_heads": 71, | |
| "num_hidden_layers": 32, | |
| "num_kv_heads": 71, | |
| "num_ln_in_parallel_attn": null, | |
| "parallel_attn": true, | |
| "quantization_config": { | |
| "_load_in_4bit": true, | |
| "_load_in_8bit": false, | |
| "bnb_4bit_compute_dtype": "float16", | |
| "bnb_4bit_quant_storage": "uint8", | |
| "bnb_4bit_quant_type": "nf4", | |
| "bnb_4bit_use_double_quant": false, | |
| "llm_int8_enable_fp32_cpu_offload": false, | |
| "llm_int8_has_fp16_weight": false, | |
| "llm_int8_skip_modules": null, | |
| "llm_int8_threshold": 6.0, | |
| "load_in_4bit": true, | |
| "load_in_8bit": false, | |
| "quant_method": "bitsandbytes" | |
| }, | |
| "rope_scaling": null, | |
| "rope_theta": 10000.0, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.41.2", | |
| "use_cache": false, | |
| "vocab_size": 65024 | |
| } | |