Instructions to use TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ with Transformers:

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

pipe = pipeline("text-generation", model="TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ")
model = AutoModelForMultimodalLM.from_pretrained("TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ

SGLang

How to use TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ 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 "TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ" \
    --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": "TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ",
		"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 "TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ" \
        --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": "TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ with Docker Model Runner:
```
docker model run hf.co/TheBloke/CollectiveCognition-v1.1-Mistral-7B-GPTQ
```

TheBloke commited on Oct 5, 2023

Commit

bab72bd

1 Parent(s): 59076e2

Fix tokenizer files

Browse files

Files changed (2) hide show

tokenizer.json +0 -0
tokenizer_config.json +8 -11

tokenizer.json ADDED Viewed

The diff for this file is too large to render. See raw diff

tokenizer_config.json CHANGED Viewed

@@ -4,25 +4,25 @@
   "added_tokens_decoder": {
     "0": {
       "content": "<unk>",
-      "lstrip": true,
       "normalized": false,
-      "rstrip": true,
       "single_word": false,
       "special": true
     },
     "1": {
       "content": "<s>",
-      "lstrip": true,
       "normalized": false,
-      "rstrip": true,
       "single_word": false,
       "special": true
     },
     "2": {
       "content": "</s>",
-      "lstrip": true,
       "normalized": false,
-      "rstrip": true,
       "single_word": false,
       "special": true
     }
@@ -37,9 +37,6 @@
   "sp_model_kwargs": {},
   "spaces_between_special_tokens": false,
   "tokenizer_class": "LlamaTokenizer",
-  "tokenizer_file": "/home/teknium/.cache/huggingface/hub/models--mistralai--Mistral-7B-v0.1/snapshots/f966a600a1f2c35a067dcb16b24bbf9ac3b85799/tokenizer.json",
-  "trust_remote_code": false,
   "unk_token": "<unk>",
-  "use_default_system_prompt": true,
-  "use_fast": true
-}

   "added_tokens_decoder": {
     "0": {
       "content": "<unk>",
+      "lstrip": false,
       "normalized": false,
+      "rstrip": false,
       "single_word": false,
       "special": true
     },
     "1": {
       "content": "<s>",
+      "lstrip": false,
       "normalized": false,
+      "rstrip": false,
       "single_word": false,
       "special": true
     },
     "2": {
       "content": "</s>",
+      "lstrip": false,
       "normalized": false,
+      "rstrip": false,
       "single_word": false,
       "special": true
     }
   "sp_model_kwargs": {},
   "spaces_between_special_tokens": false,
   "tokenizer_class": "LlamaTokenizer",
   "unk_token": "<unk>",
+  "use_default_system_prompt": true
+}