Instructions to use tsuyuan/Llama-2-7b-unit_random_embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tsuyuan/Llama-2-7b-unit_random_embed with Transformers:

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

pipe = pipeline("text-generation", model="tsuyuan/Llama-2-7b-unit_random_embed")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tsuyuan/Llama-2-7b-unit_random_embed")
model = AutoModelForCausalLM.from_pretrained("tsuyuan/Llama-2-7b-unit_random_embed")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use tsuyuan/Llama-2-7b-unit_random_embed with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tsuyuan/Llama-2-7b-unit_random_embed"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tsuyuan/Llama-2-7b-unit_random_embed",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/tsuyuan/Llama-2-7b-unit_random_embed

SGLang

How to use tsuyuan/Llama-2-7b-unit_random_embed 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 "tsuyuan/Llama-2-7b-unit_random_embed" \
    --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": "tsuyuan/Llama-2-7b-unit_random_embed",
		"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 "tsuyuan/Llama-2-7b-unit_random_embed" \
        --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": "tsuyuan/Llama-2-7b-unit_random_embed",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use tsuyuan/Llama-2-7b-unit_random_embed with Docker Model Runner:
```
docker model run hf.co/tsuyuan/Llama-2-7b-unit_random_embed
```

tsuyuan commited on Aug 22, 2023

Commit

f4b09a4

1 Parent(s): 142eed7

Upload tokenizer

Browse files

Files changed (2) hide show

special_tokens_map.json +3 -3
tokenizer_config.json +5 -4

special_tokens_map.json CHANGED Viewed

@@ -2,14 +2,14 @@
   "bos_token": {
     "content": "<s>",
     "lstrip": false,
-    "normalized": true,
     "rstrip": false,
     "single_word": false
   },
   "eos_token": {
     "content": "</s>",
     "lstrip": false,
-    "normalized": true,
     "rstrip": false,
     "single_word": false
   },
@@ -18,7 +18,7 @@
   "unk_token": {
     "content": "<unk>",
     "lstrip": false,
-    "normalized": true,
     "rstrip": false,
     "single_word": false
   }

   "bos_token": {
     "content": "<s>",
     "lstrip": false,
+    "normalized": false,
     "rstrip": false,
     "single_word": false
   },
   "eos_token": {
     "content": "</s>",
     "lstrip": false,
+    "normalized": false,
     "rstrip": false,
     "single_word": false
   },
   "unk_token": {
     "content": "<unk>",
     "lstrip": false,
+    "normalized": false,
     "rstrip": false,
     "single_word": false
   }

tokenizer_config.json CHANGED Viewed

@@ -5,7 +5,7 @@
     "__type": "AddedToken",
     "content": "<s>",
     "lstrip": false,
-    "normalized": true,
     "rstrip": false,
     "single_word": false
   },
@@ -14,20 +14,21 @@
     "__type": "AddedToken",
     "content": "</s>",
     "lstrip": false,
-    "normalized": true,
     "rstrip": false,
     "single_word": false
   },
-  "legacy": true,
   "model_max_length": 1000000000000000019884624838656,
   "pad_token": null,
   "sp_model_kwargs": {},
   "tokenizer_class": "LlamaTokenizer",
   "unk_token": {
     "__type": "AddedToken",
     "content": "<unk>",
     "lstrip": false,
-    "normalized": true,
     "rstrip": false,
     "single_word": false
   }

     "__type": "AddedToken",
     "content": "<s>",
     "lstrip": false,
+    "normalized": false,
     "rstrip": false,
     "single_word": false
   },
     "__type": "AddedToken",
     "content": "</s>",
     "lstrip": false,
+    "normalized": false,
     "rstrip": false,
     "single_word": false
   },
+  "legacy": false,
   "model_max_length": 1000000000000000019884624838656,
   "pad_token": null,
+  "padding_side": "right",
   "sp_model_kwargs": {},
   "tokenizer_class": "LlamaTokenizer",
   "unk_token": {
     "__type": "AddedToken",
     "content": "<unk>",
     "lstrip": false,
+    "normalized": false,
     "rstrip": false,
     "single_word": false
   }