Instructions to use ccore/llama-2-1.1B-Rhetorical-Agents with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ccore/llama-2-1.1B-Rhetorical-Agents with Transformers:

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

pipe = pipeline("text-generation", model="ccore/llama-2-1.1B-Rhetorical-Agents")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("ccore/llama-2-1.1B-Rhetorical-Agents")
model = AutoModelForMultimodalLM.from_pretrained("ccore/llama-2-1.1B-Rhetorical-Agents")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ccore/llama-2-1.1B-Rhetorical-Agents with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ccore/llama-2-1.1B-Rhetorical-Agents"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ccore/llama-2-1.1B-Rhetorical-Agents",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ccore/llama-2-1.1B-Rhetorical-Agents

SGLang

How to use ccore/llama-2-1.1B-Rhetorical-Agents 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 "ccore/llama-2-1.1B-Rhetorical-Agents" \
    --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": "ccore/llama-2-1.1B-Rhetorical-Agents",
		"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 "ccore/llama-2-1.1B-Rhetorical-Agents" \
        --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": "ccore/llama-2-1.1B-Rhetorical-Agents",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ccore/llama-2-1.1B-Rhetorical-Agents with Docker Model Runner:
```
docker model run hf.co/ccore/llama-2-1.1B-Rhetorical-Agents
```

ccore commited on Sep 30, 2023

Commit

65e353a

1 Parent(s): 15b4045

Update README.md

Browse files

Files changed (1) hide show

README.md +2 -44

README.md CHANGED Viewed

@@ -11,48 +11,6 @@ model-index:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
-tinyllama base 55k steps
-# core61
-This model is a fine-tuned version of [core6/](https://huggingface.co/core6/) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.6814
-- Accuracy: 0.6489
-## Model description
-More information needed
-## Intended uses & limitations
-More information needed
-## Training and evaluation data
-More information needed
-## Training procedure
-### Training hyperparameters
-The following hyperparameters were used during training:
-- learning_rate: 0.001
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
-- gradient_accumulation_steps: 8
-- total_train_batch_size: 64
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 1.0
-### Training results
-### Framework versions
-- Transformers 4.34.0.dev0
-- Pytorch 2.0.1+cu117
-- Datasets 2.14.5
-- Tokenizers 0.13.3

 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
+tinyllama base 55k steps test
+test was private, i release :D