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

Libraries

How to use jdakillah/Generalbot with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="jdakillah/Generalbot")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jdakillah/Generalbot")
model = AutoModelForCausalLM.from_pretrained("jdakillah/Generalbot", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jdakillah/Generalbot with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jdakillah/Generalbot"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jdakillah/Generalbot",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/jdakillah/Generalbot

SGLang

How to use jdakillah/Generalbot 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 "jdakillah/Generalbot" \
    --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": "jdakillah/Generalbot",
		"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 "jdakillah/Generalbot" \
        --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": "jdakillah/Generalbot",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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

jdakillah commited on Jan 16, 2023

Commit

600db4e

1 Parent(s): 915160f

Delete config.json

Browse files

Files changed (1) hide show

config.json +0 -54

config.json DELETED Viewed

@@ -1,54 +0,0 @@
-{
-  "activation_dropout": 0.0,
-  "activation_function": "gelu",
-  "add_bias_logits": false,
-  "add_final_layer_norm": true,
-  "architectures": [
-    "BlenderbotForConditionalGeneration"
-  ],
-  "attention_dropout": 0.0,
-  "bos_token_id": 1,
-  "classif_dropout": 0.0,
-  "d_model": 2560,
-  "decoder_attention_heads": 32,
-  "decoder_ffn_dim": 10240,
-  "decoder_layerdrop": 0.0,
-  "decoder_layers": 24,
-  "dropout": 0.1,
-  "encoder_attention_heads": 32,
-  "encoder_ffn_dim": 10240,
-  "encoder_layerdrop": 0.0,
-  "encoder_layers": 2,
-  "eos_token_id": 2,
-  "extra_layer_norm": false,
-  "extra_pos_embeddings": 0,
-  "force_bos_token_to_be_generated": false,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2"
-  },
-  "init_std": 0.02,
-  "is_encoder_decoder": true,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2
-  },
-  "length_penalty": 0.65,
-  "max_length": 60,
-  "max_position_embeddings": 128,
-  "min_length": 20,
-  "model_type": "blenderbot",
-  "no_repeat_ngram_size": 3,
-  "normalize_before": true,
-  "normalize_embedding": false,
-  "num_beams": 10,
-  "num_hidden_layers": 2,
-  "pad_token_id": 0,
-  "scale_embedding": true,
-  "static_position_embeddings": false,
-  "unk_token_id": 3,
-  "layernorm_variant": "prelayernorm",
-  "vocab_size": 8008
-}